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08:30-09:30 Session 5: Plenary - Richard Parry Jones
Research Challenges for Control Systems Engineering in Road and Rail
10:00-12:00 Session 6A: IMechE Mini Symposium - Unmanned Aircraft Systems
Advanced UAS technologies for aerial manipulation and landing on mobile platforms
Bio-Inspired Flight Control Systems for UAS
SPEAKER: Ian Cowling
VTOL flying wing control systems development
Civil UAV applications Using Crowd-sourced Imagery Analysis
SPEAKER: Darren Ansell

ABSTRACT. This presentation describes the cross-disciplinary ‘Aerosee’ project, involving UCLan’s School of Computing, Engineering and Physical Sciences and Media Innovation Studio, along with commercial firm eMigs. Aerosee is unique in uniting Unmanned Aerial Vehicle technology with the ‘power of the crowd’. It capitalises on some of the key attributes of the burgeoning UAV technology field, and examine how the devices can be used for socially-motivated purposes, such as by the emergency services. The presentation will discuss the first trial which explored how the use of UAV (or ‘Drone’) technology, together with ‘crowd-sourced’ imagery analysis can reduce the time taken to locate and rescue a person in distress.

Research and Test Environment for Unmanned Aircraft Systems
10:00-12:00 Session 6B: IET Mini Symposium - Monitoring and control of poorly-defined and uncertain systems
The smart grid – essential contribution to efficiency or Achilles heel of a future electricity system?
SPEAKER: Roger Kemp

ABSTRACT. The principles behind Britain’s electricity system have been largely unchanged for a century. Steam turbines were demonstrated by Sir Charles Parsons in 1884 and, in Edwardian times, Charles Merz established an ac grid in Newcastle on Tyne distributing power at 5.5 kV, three-phase. The present grid, although hundreds of times larger, uses basically the same technology.

The Climate Change Act 2008 and the Industrial Emissions Directive 2010/75/EU have triggered a paradigm shift in this system. So far, we have seen only small changes but plans for phasing-out coal-fired power stations and the widespread adoption of renewable energy will radically change the way electricity is generated and used. Instead of the flow of energy being from a few dozen large centralised power stations via high voltage grids to millions of consumers, we will have generation that includes thousands of wind turbines and millions of solar panels, feeding into the 11 kV and 400 V distribution networks. In addition, we can expect to see millions of electric vehicles, each having a high-capacity battery charger, and a wholesale switch from gas central heating to electrically-powered heat pumps which could double the peak load on the grid.

Since the 1950s, electricity generation policy has been “predict and provide”. Consumers do not have to think about when they switch on the kettle; there will always be enough electricity. However to continue this policy when much of the generating capacity uses renewable energy, that is only available when the sun shines or the wind blows, and when loads such as electric vehicle chargers could equally well be supplied at 3 am, rather than when the driver happens to return from work, would be horrendously expensive. Luckily the smart grid can come to the rescue!

No-one has really defined what a smart grid is – or to be more accurate, thousands of people have defined it to themselves and made the assumption that their understanding is the same as for everyone else. The common assumption is that it is (or will be) some form of intelligent network that recognises when electricity is in short supply and reduces the demand from loads that can readily be cut off for a period. Other visions of a smart grid include the capability to modulate the output of solar panels or trigger reverse power flows in EV battery chargers (vehicle-to-grid or V2G) to compensate for a sudden loss of supply. Companies are already marketing home energy management computers that allow consumers to control loads remotely via an App on their phones.

However there are downsides: if the smart grid sends a message to a million 5 kW battery chargers, sold with a default setting of 10 p/kWh, that electricity prices have dropped from 11 to 9 p/kWh, the surge in demand could destabilise the system – any feedback system with unquantifiable delays risks instability. An erroneous message asking V2G battery chargers over a wide area to provide power could defeat protection systems.

Attacks on a smart grid are also a possibility. With household energy bills more than £1000 p.a. there is an incentive to buy black market software that hacks into a smart meter – and less risky than a pair of crocodile clips in the meter terminal box. During the 1939-45 war, both sides sent waves of bombers to damage power stations. In a future conflict the task could be achieved more easily and surreptitiously by the equivalent of the Stutnix virus, used against Iranian centrifuges.

Without smart grids we are unlikely to be able to meet our climate change emissions targets. With them we may be introducing instability or opportunities for malicious intervention that causes disruption to power supplies. How do we weigh the risks of a technology for which we do not even have a shared definition?

Challenges for monitoring and controlling biological systems

ABSTRACT. Thanks to the (r)evolution in sensors and computing power, the possibilities for measuring and processing biological signals in real-time are ever growing. As a consequence, it becomes more and more realistic to apply schemes of model-based monitoring and control to biological systems in practice. However, unlike many mechanical systems, biological systems are very complex, individually different, time-varying and dynamic, making the management of these systems often very challenging.

A first challenge is to model these biological systems using compact, accurate and biologically meaningful models that can be applied in monitoring and controlling schemes. It is argued that dynamic data-based mechanistic modelling approaches are potential candidates for model-based management of biological systems. A second challenge is to extract model features that can be used as biomarkers for monitoring the status of individual biological systems. A third challenge is to define proper control targets that take into account the physiological/physical boundary conditions of the considered biological system. Examples of animal and human applications, ranging from cellular up to ecosystem level, will be discussed.

Poorly-Defined Environmental Systems: Data-Based Mechanistic Modelling, Forecasting and Control
SPEAKER: Peter Young

ABSTRACT. Engineering is basically about the way humans apply their knowledge to design, build and maintain objects of various kinds. Although engineering research can take various forms, depending on what branch of engineering we are considering, it normally conforms to the `scientific method', following what Popper (1959) has termed a ‘hypothetico-deductive’ procedure. There is, however, an important difference between such standard engineering research and research based on the application of engineering principles and methods to naturally occurring environmental systems (recently termed Geoegineering). Natural systems are not made by humans: they may be shaped and modified by us but we did not create them and so, in contrast to normal engineering constructs, their internal behavioural mechanisms are quite often poorly defined and understood.

The climate scientist, for instance, can hypothesize about the causes and mechanisms of `global warming' but it is clear from the controversy on this topic, that such hypotheses are not universally accepted. Moreover, while Popper stresses the importance of planned experimentation in hypothetico-deductive reasoning, it is rarely possible to conduct well planned experiments on natural systems in order to remove ambiguity and so clarify our understanding. An alternative, systems-based approach is to observe the normal operational behaviour and try to infer the most important underlying mechanisms from such observational data and our, hopefullly inspired, perceptions of what these dominant mechanisms may be. Such data-based analysis is the domain of `inductive' or `hypothetico-inductive' reasoning (see e.g. Young, 2013), in which the modelling is based on model structures that are initially identified from the naturally occurring data, thus avoiding undue reliance on prior hypotheses and ensuring that the resulting models are fully identifiable from the available data.

This seminar will outline a particular hypothetico-inductive approach to the modelling, forecasting and control of environmental systems and show how this Data-Based Mechanistic (DBM) procedure (see e.g. Young 1998, 2011 and the prior references therein) has been applied in a study of globally averaged climate data. It will show how the behaviour of the large simulation models produced by climate scientists is much simpler than their size and complexity would suggest. In particular, the globally averaged response characteristics of even the largest climate models, the Global Circulation Models (GCMs), are defined almost completely by a relatively small number of `dominant modes'; and it is these dominant modes of behaviour that are most important in forecasting and control system design.

10:00-12:00 Session 6C: Special Session - Automotive Control
Optimal Control of the 2014 Formula One Power Train

ABSTRACT. We study the optimal control of the 2014 Formula One power train in order to achieve minimum lap times on the Spa circuit, which is modelled in three dimensions. Apart from controlling the steering, engine fuelling and the braking system, we make optimal use of the kinetic and thermal energy recovery systems. Results during both racing and qualifying will be presented and analysed.

Information fusion for vehicular systems parameter estimation using an extended regressor in a finite time estimation algorithm

ABSTRACT. In this paper, we present an extension to a recently developed continuous-time, finite-time parameter estimation structure to perform data fusion. The regression elements of the finite-time algorithm are used to carry additional information. Their parameters are also parameters in the dynamics of additional sensors. This additional information will help in estimating these parameters. The algorithm can easily augment an adaptive observer. This new data fusion structure is employed in the context of vehicle mass and road gradient estimation. The estimator in its original form makes use of vehicle speed over ground and driving force information and the modification is demonstrated with the inclusion of an accelerometer aligned to the longitudinal direction in the vehicle frame of reference. Such an accelerometer could be part of the array in an onboard IMU like those used to control vehicle safety systems, whose outputs are broadcast on the onboard vehicle CAN bus. The modified algorithm has been tested with practically relevant data, confirming that the new technique produces numerically correct results and significantly improves parameter estimates over the algorithm in its existing form.

Sensor Configurations and Testbed for Vehicle State Estimation
SPEAKER: unknown

ABSTRACT. This paper conducts an investigation on whether vehicle dynamic states such as pitch, roll, yaw, and particularly sideslip, can be estimated using limited and inexpensive automotive-grade sensors without the use of model based estimators (parameter free). First, multiple sensors and combinations of these sensors are evaluated for the purpose of estimating vehicle states with different levels of accuracy. Second, experimental tests are carried out on a purpose built vehicle. As most commercial vehicles come equipped with an Accelerometer and Gyroscope (INS), we use this sensor combination along with a single antenna GPS receiver for our tests. The state estimation algorithms for the given sensor combination are implemented in a dSPACE MicroAutoBox that allows real-time computation. The test vehicle is a high-power radio-controlled car, which also carries a commercial data logger that is used to set a benchmark for the estimated states.

Equivalent Circuit Model Estimation of Induction Machines under Elevated Temperature Conditions

ABSTRACT. This paper explores performing identifiability analysis on the equivalent circuit model (ECM) parameters of an electric machine (EM) using its impedance response. When modelling the ECM of an EM for room temperature conditions, some of the ECM parameters can be obtained from the manufacturer’s data. However, as the temperature of an EM increases this significantly changes the underlying physics (resistivity, capacitance and inductance) of machine parameters, therefore the manufacturers data become inaccurate for equivalent circuit modelling purposes. ECM parameters need to be obtained from the frequency response under the different temperature conditions. To achieve this a nonlinear optimisation scheme with constraints is proposed for the purpose of ECM parameter identification, whereby a temperature-dependent ECM is derived. This work has important applications in EM design and condition monitoring and provides a valuable precursor towards developing age-dependent models.


A Gamma-Z -source Based Hybrid Power Converter for Battery-Fuel Cell Hybrid Electric Vehicle
SPEAKER: unknown

ABSTRACT. Low cost and high reliability are the main issues considered in power converter design for hybrid electric vehicle. In this paper, a new hybrid power converter is proposed for the power flow control of battery fuel cell hybrid electric vehicle. The converter consists of a unidirectional Gamma-Z-source converter and a bidirectional DC-DC converter. By controlling the voltage of the Z source capacitor and the modulation index of the inverter, the power flow between the fuel cell, battery and the load can be controlled flexibly. The different operation modes of the system and the power flow control strategies are analysed. To verify the validity of the proposed power converter topology and the control methods, system simulation model is developed in Matlab/Simulink environment. In addition, the simulation model is also implemented in the RT-LAB real-time simulator. The simulation results demonstrated the feasibility of the proposed methods.

Product innovation by identifying customers hidden needs
SPEAKER: Naseem Akhtar

ABSTRACT. A method has been used to elicit the hidden needs of customers. Their input is then used to generate innovative ideas that will be used for product features development. The paper demonstrates the effectiveness of the techniques in comparison with using traditional techniques where customers input are gathered by asking them about the technical features. The traditional techniques result in developing ‘me too’ products and whereas our method delivers radical features. The results are used for carrying out competitive analysis and identifying the market gaps.

10:00-12:00 Session 6D: Invited Session - Integrated Operation in Large Scale Industrial Sites, Results from the Energy-Smartops Consortium

ABSTRACT. The early detection and diagnosis of faults can improve the energy efficiency of industrial processes by avoiding the inefficient operation of faulty equipment as well as minimizing unplanned shutdowns, downtime and extensive damage to other parts of the system. In addition, industrial needs are evolving fast towards more flexible schemes. As a consequence, it is often required to adapt the plant production to the demand, which can be volatile depending on the application. This is why it is important to develop tools that can monitor the condition of the process working under varying operational conditions. Canonical Variate Analysis (CVA) is a multivariate data driven methodology that can be applied to detect and diagnose faults in industrial systems. This method has the ability to capture the process dynamics more efficiently than other similar data driven algorithms. The aim of this work is to provide a benchmark case to demonstrate the ability of CVA to detect and diagnose artificially seeded faults in a large scale test rig and measure the impact of those faults on the system performance, in particular its energy efficiency. The results obtained suggest that CVA can be effectively used for fault detection using real process data. The faults introduced were successfully detected in the early stages of degradation, and the source of the faults was identified using contribution plots.

Fault Detection in Electric Motors by means of the Extended Kalman Filter as Disturbance Estimator

ABSTRACT. In this paper, an approach for disturbance estimation in the stator phase currents of an induction machine is presented. The approach is based on the Extended Kalman Filter that uses the extended model of an electrical induction machine (IM) under healthy conditions. The extended model includes additional states (disturbances) that allow discrepancies between the model and the real system to be detected. It is demonstrated through simulation that the method is able to identify anomalies when unmodelled dynamics are induced. Subsequently, the values of the estimated disturbances may be used as inputs to a condition monitoring system in order to detect machine faults, helping to reduce the rate of spurious stops and false alarms, therefore improving the overall process efficiency. Additionally, the disturbances could be taken into account in the control system of the motor improving the machine performance.

Preprocessing of Raw Data for Developing Steady-State Data-Driven Models for Optimizing Compressor Stations

ABSTRACT. Compressors operate in parallel to increase the supply of a gas in many applications in process industries. A typical example is a network of compressors providing compressed air to an air separation process. To optimally distribute the load of the compressors in parallel, an optimization problem is formulated that takes into account the operational constraints (performances and physical limits) of the compressors and the objective is to reduce operational costs, i.e. power consumption of the drivers of the compressors. The optimization takes place when the system is in steady state. The structure of the optimization employs steady-state data-driven models to represent the operation in steady-state. Many researchers reported that the identification of steady-states of the data plays a key role for accurate representation of the actual process by a data-driven model. However, to the best of the authors’ knowledge, there is not much research on the quantification of the influence of the output of the steady state detection methods on the data-driven models. For these reasons there is a need to examine this topic.

An integrated control technique for compressor operation
SPEAKER: Sara Budinis

ABSTRACT. In the gas industry the control of the compression system has two primary objectives: the operation of the machine and also its protection against damage such as that following a surge cycle. The interaction between these two control actions can be strong, causing instability and oscillations. Moreover whenever the gas is recycled for surge protection, it is not delivered as final product and energy is wasted during its compression [1]. These observations provide the incentive for better integrated control. While many researchers have been working on the control of surge, not much has been done to improve the control of the performance or the integration between the two control objectives, even though this need has already been highlighted in the past [2]. This paper proposes an integrated control scheme based on the characteristic map of the compressor, taking into account inlet disturbances. The proposed control solution is comparable to the state-of-the-art control solution under slow disturbance dynamics and allows a tighter pressure control during fast changing dynamics, reducing at the same time the proximity to the surge region.

[1] F. B. Horowitz, B. P. Gupta, and B. G. Liptak, "Compressor Control and Optimization," in Instrument Engineers' Handbook. vol. 2, B. G. Liptak, Ed., 4th ed Boca Raton, FL: Taylor & Francis Group, 2006, pp. 1763-1793. [2] F. Willems and B. de Jager, "Modeling and control of compressor flow instabilities," IEEE Control Systems Magazine, vol. 19, pp. 8-18, Oct 1999.

Multicriteria diagnosis of synchronous machines: rotor-mounted sensing system.

ABSTRACT. As a part of an extended research on synchronous machines, a new technique applied to a rotor-mounted sensing system will be introduced. The capabilities of sensing the physical variables over the rotor are quite promising. A 7.5 kW 4 salient-pole synchronous machine with configurable fault scenarios is available for this research. The measurements in the rotor are taken through two sets of 25 slip-rings expressly mounted for this purpose. The sensors installed are four thermocouples, one on each pole; two analog Hall Effect sensors each centered on the surface of a north and south electrical pole; two more at the end and front ring of the damping cage to measure the current flowing over. The last capability of this system is to measure the current flowing over the damping cage bars. Having more reliable and precise condition monitoring systems will make it possible to define the assessment of the machine with more accuracy. Consequently, making this information available for the operation and maintenance scheduling of industrial plants will lead to more efficient processes through improved operation schemes according to the actual status of the system.

12:45-13:45 Session 7: Plenary - Geoff Downton
Drilling and Control
SPEAKER: Geoff Downton

ABSTRACT. Within a tick of the imperceptibly slow moving geological clock, a borehole is plunged deep into the Earth. How we steer the ensuing transient response of the rocks and the fluids towards a safe and beneficial outcome is at the very heart of the drilling process. Wells are being drilled deeper and faster and in more difficult environments, and so the complexity of the interactions between different domains of physics is increasing. Fortunately, this is a challenge well suited to the interests and tools of the control engineering community. The “factory floor” of a well is clearly very long and very thin—effectively a line along which the mechanical drilling string and the hydraulic drilling fluids must transmit  power, information and control to propagate the borehole to its target resting place. The Earth needs to be persuaded to reveal its structural secrets, and so long arrays of sensors and actuators follow the drill bit into the ground to illuminate, monitor and control the path to be drilled. In comparison to the drilling industry, the downstream processing industries are highly automated. A chemical plant designer has great freedom to create the ideal production environment. Such is not the case for drilling. The impetus for control engineers to take an interest in drilling has been further strengthened by a drive to increase the level of automation for the standard reasons of efficiency, consistency, performance and management of complexity. This drive for controlled drilling presents both challenges and opportunities.


14:00-16:00 Session 8A: InstMC Mini Symposium - Actively Controlled Automotive Safety Systems
From ADAS to the fully autonomous vehicle: What is the reality?
SPEAKER: Alain Dunoyer

ABSTRACT. The presentation will provide an overview of the ADAS development over the last 20 years. The current landscape will be explained together with the likely future scenarios in terms of further level of automation deployment. The main sensing technologies together with their pros and cons will be explained. Finally, the hurdles towards even higher automation levels will be discussed.

Review of automotive control and ISO26262
SPEAKER: Paul King

ABSTRACT. ISO26262 ("Road vehicles – Functional safety") is an Automotive Functional Safety standard which was first published on November 2011. It's main aim is to provide a standard by which anyone developing road vehicle electronic and electrical systems can address possible hazards caused by their malfunction. The standard covers a wide range of areas including automotive development safety lifecycle, Functional Safety and automotive-specific risk-based approach for determining risk classes (Automotive Safety Integrity Levels, ASILs). 

In this presentation we will review a couple of automotive functions and how the ASIL categorisation and the standard has then effected their control and fault detection designs. We will also develop a simple automotive controller and show more advanced control strategies can be employed to meet these design requirements laid out in the standard.

A survey of vehicle tyre pressure detection methods and related legislation
SPEAKER: unknown

ABSTRACT. This presentation examines the problem of detecting tyre pressure in a stationary and moving vehicle. A brief outline of the historical background to the motivation and legislation is given with an analysis of the different methods that have been proposed. The methods can generally be divided into two distinct groups, namely direct and indirect measurement and estimation.

Active buckling control for vehicle body structures: A demonstration of the approach
SPEAKER: unknown

ABSTRACT. This presentation introduces the concept of actively controlled mechanical structures. New emerging technologies allow for the introduction of actively controlled self-preserving mechanical structures with embedded functionality. A robust decision maker can be applied to an active structure, allowing the mechanical properties to be altered, effectively cancelling or at least reversing undesirable scenarios.    

Prompted by the compatibility issues arising when vehicles of dissimilar masses collide, the need for active buckling control is demonstrated. Active buckling control is achieved through the use of actively controlled materials, whereby the mechanical properties of a structure can be changed. The purpose of such a system allows for the buckling point to be controlled, effectively altering the collision energy absorbed between the vehicles. Hence, stiffening the more vulnerable vehicle and reducing the energy absorbed by that vehicle; as a result, sharing the collision energy more appropriately and improving the safety of the occupants. The approach demonstrated can be applied to numerous other applications, such as controlling the dynamic response that tall buildings and large bridges encounter from earth quakes or strong winds. As a result, future mechanical structures can be developed that are significantly lighter, more adaptive and efficient. 


The Development of Euro NCAP AEB test procedures for Cars and Vulnerable Road Users
SPEAKER: Matthew Avery

ABSTRACT. Autonomous Emergency Braking systems use sensors to identify imminent collision threats ahead of the vehicle and then automatically apply braking to help avoid a collision, or to mitigate it’s severity. AEB systems can not only work with vehicles ahead, but some are also capable of responding to pedestrians. AEB has been shown by several international studies to be effective in reducing collisions, for both damage and injuries. The aim of the test procedures developed by Thatcham Research is to encourage adoption of AEB as standard fit on vehicles, and to raise consumer awareness of this beneficial technology.

Thatcham has used a real world accidentology study to identify the most common front-into-rear collision scenarios to generate a test procedure for these AEB systems. Suitable collision targets (a car and a pedestrian) have been developed that are realistic, representative and capable of withstanding repeated impacts. The accompanying scoring systems have been generated to distinguish better/worse performance of the AEB systems. These AEB tests have been adopted in the UK insurance group rating system, and also in Euro NCAP’s consumer safety ratings.

Session summary and round up
SPEAKER: Keith Burnham
14:00-16:00 Session 8B: IChemE Mini Symposium - Industrial Process Control: Latest Challenges and Applications
Innovation Still Required to Solve Upstream Oil & Gas Control Issues
SPEAKER: Paul Oram
Practical problems in implementing small scale MBPC in the chemical industry
SPEAKER: Dave Lovett
Making predictive control easier and cheaper to implement
14:00-16:00 Session 8C: Invited Session - Sustainable Control of Off-shore Wind Turbines
Introduction to Session - Sustainable Control of Off-shore Wind Turbines
SPEAKER: Ron Patton

ABSTRACT. The control and fault monitoring of offshore wind turbines with rotor diameters of the order of 100m is a very challenging application subject. Situated at sea the wind turbines operate under difficult conditions with costly access for maintenance. The requirements for reliable and sustainable wind farm operation mean that control systems must be fault-tolerant and continue operating with acceptable performance when some faults occur. This session is concerned with the description of design methods of fault tolerant control evaluated on advanced wind turbine benchmark facilities within consortia involving industry and academia.

Fault Reconstruction using a Takagi-Sugeno Sliding Mode Observer for the Wind Turbine Benchmark
SPEAKER: Sören Georg

ABSTRACT. In this paper, a Takagi-Sugeno sliding mode observer is designed to detect, isolate and reconstruct three different sensor faults and an actuator fault in a specified wind turbine benchmark problem. An extension of the discontinuous observer term using a weighted combination of gains responsible for establishing the sliding motion is proposed. The weights are equivalent to the membership functions of the Takagi-Sugeno (TS) model of the wind turbine. This approach enables new design possibilities for sliding mode observer if the matrices of each local model of the TS model differ significantly. The effectiveness of the design approach is demonstrated by simulation results for fault scenarios defined in the wind turbine benchmark.

Trajectory-based fault accommodation in Wind Turbine Systems
SPEAKER: Joseph Yamé

ABSTRACT. This paper presents a trajectory-based mechanism to tolerate faults occurring in a Wind Turbine (WT) system. The system is a benchmark WT model which includes FAST coded simulator designed by the U.S. National Renewable Energy Laboratory's. In the proposed mechanism, no \textit{a priori} information about the model of the turbine is used in real-time. In fact, we use online measurements generated by the WT. These online measurements captures the “behaviour” of the wind turbine. Based on the given control specifications, and the observed measurements an occurring fault is accommodated by reconfiguring the controller such that the WT generates the rated power even under faulty conditions. In addition, no use of an explicit fault-diagnosis module is seen in this approach.

A Robust Adaptive Approach to Wind Turbine Pitch Actuator Component Fault Estimation
SPEAKER: Ronald Patton

ABSTRACT. Motived by wind turbine pitch actuator component fault estimation problem, a robust adaptive fault estimation procedure is proposed in this paper. The estimation of a component fault which is a multiplicative fault, is not as straightforward a problem as the estimation of an additive fault. The proposed fault estimator is based on an adaptive observer structure where the observer gain and adaptive law are computed using linear matrix inequality (LMI) and linear parameter varying (LPV) techniques. Both wind turbulence and sensor noise are considered as external disturbances. The simulation results show the usefulness and effectiveness of the proposed approach.

Wind Speed Estimation in Wind Turbines using EKF: Application to Experimental Data
SPEAKER: Vicenç Puig

ABSTRACT. Wind speed estimation is an important issue when addressing the control or the monitoring of a wind turbine. A realistic value of wind speed could be very useful to improve performance of wind turbine controllers, either for scheduling or as an extra feed forward term. In addition, it could also be useful for fault diagnosis and fault-tolerant control of the wind turbine. The objective of this work is to design and implement a wind speed estimator based on an Extended Kalman Filter (EKF) that uses a simplified nonlinear model and to compare the performance with experimental wind speed measurements. Even with such a simple model, the agreement with experimental data is significant, and shows great potential to be used by an advanced wind turbine controller.


Sensor Fault Tolerant Control of a Wind Turbine via Takagi-Sugeno Fuzzy Observer and Model Predictive Control
SPEAKER: Xiaoran Feng

ABSTRACT. This paper proposes an approach to fault tolerant control (FTC) of a wind turbine subject to sensor faults. Both analytical and hardware redundancies are utilized in this approach. A residual generator based on a Takagi-Sugeno (T-S) fuzzy observer is proposed as the fault detection and identification (FDI) unit. A T-S fuzzy observer design method via online eigenvalue assignment is proposed. It is shown that single residual can be utilized to identify different sensor faults by analyzing the characteristics of the residual. Model predictive control (MPC) based on T-S fuzzy modeling is proposed as the wind turbine controller to take into account the turbine system nonlinearity and physical constraints of the turbine actuators.

Fault Tolerant Control of an Offshore Wind Turbine Model via Identified Fuzzy Prototypes
SPEAKER: Silvio Simani

ABSTRACT. In order to improve the safety, the reliability, the efficiency, and the sustainability of offshore wind turbine installations, thus avoiding expensive unplanned maintenance, the accommodation of faults in their earlier occurrence is fundamental. Therefore, the main contribution of this work consists of the development of a fault accommodation scheme applied to the control of a wind turbine nonlinear model. In particular, a data– driven strategy relying on fuzzy models is exploited to build the fault tolerant control scheme. Fuzzy theory is exploited here since it allows to approximate easily the unknown nonlinear model and manage uncertain data. Moreover, the fuzzy prototypes, which are directly identified from the wind turbine measurements, provide the reconstruction of the considered faults, thus leading to the direct design of the fault tolerant control module. In general, the nonlinearity of wind turbine system could generate complex analytic solutions. This aspect of the work, followed by the simpler strategy relying on fuzzy prototypes, represents the key point when on–line implementations are considered for a viable application of the proposed methodology. A realistic offshore wind turbine simulator is used to validate the achieved performances of the suggested methodology. Finally, comparisons with different fault tolerant control methods serve to highlight the advantages of the suggested approach.

14:00-16:00 Session 8D: Invited Session - Real-time Adaptive Networked Control of Rescue Robots 1
The stability performances improvement through kinematic and dynamic modeling of the hopping robots

ABSTRACT. The paper presents an innovative design for a wheeled hopping robot. The main objective was to obtain a stable and efficient robot, which can jump over obstacles and has the ability to reach a certain ledge. The new design of the robot has the capability to jump to a certain distance even with a zero initial velocity provided by the wheels movement. Also, we took into consideration the wind speed which can prevent our robot to reach the desired destination, and compensated with an initial velocity on the direction of movement. For testing we designed a simulation which had as inputs different initial conditions to test and present the jumping capability of our robot in different jumping conditions. In the end we provide a jump area which the robot can reach for certain initial conditions, so we can later chose the optimal one for reaching the target position.

Haptic interfaces for the rescue walking robots motion in the disaster areas

ABSTRACT. In the recent years haptic interfaces became a reliable solution in order to solve problems which arise when humans interact with the environment. If in the research area of the haptic interaction between human and environment there are important researches, a innovative approach for the interaction between the robot and the environment using haptic interfaces and virtual projection method is presented in this paper. .In order to control this interaction we used the Virtual Projection Method where haptic control interfaces of impedance and admittance will be embedded. The obtained results, validated by simulations assure stability, stiffness, high maneuverability and adaptability for rescue walking robots in order to move in disaster, dangerous and hazardous areas.

Dynamic Analysis for the Leg Mechanism of a Wheel-Leg Hybrid Rescue Robot
SPEAKER: unknown

ABSTRACT. The inverse dynamic of the leg with a (2-UPS+U)R series-parallel mechanism of the hybrid rescue robot is analyzed in this paper. First, the constrained relationships in the leg are determined, and the 6×6 Jacobian matrices of the series-parallel leg are derived and presented. Second, the velocity, acceleration, angular velocity and acceleration of center of mass in each link are solved and the dynamic model of the series-parallel leg is established with virtual work principle and its standard Lagrange formula are presented in detail. In the end, the numerical simulation of the series-parallel leg is carried out and its dynamic results are validated with the ADAMS software. The dynamic equations of the leg lay the foundation for a number of computational algorithms that are useful in mechanical design, control, simulation, animation and built the hybrid rescue robot prototype.

Fault-Tolerant Gait for a Quadruped Robot with Partially Fault Legs

ABSTRACT. Legged robots have greater capability to traverse irregular terrains. However, one of the most common problems is the failure of the actuators when the robot is working in remote. Fault-tolerant gait about one fault actuator can be found. This paper proposes another algorithm for more than one fault actuators. The DOFs of the robot body are divided into two parts: the major DOFs, which are critical in performing a gait; and secondary DOFs. The idea of the method is to find a proper kinematic resolution to perform major DOFs by controlling the secondary DOF of the robot. Simulations and experiments are presented here on a hydraulic quadruped robot.

The Study of NAO Robot Arm Based on Direct Kinematics by Using D-H Method
SPEAKER: Shuhuan Wen

ABSTRACT. This paper presents a direct kinematics method for humanoid NAO model. Firstly, it analyses the upper limb topology of NAO model and establishes the kinematics model by using D-H method. Secondly, the homogeneous transformation matrix of upper 1imb joints of the robot is derived in this paper, which solves the position of the end of the actuator. Finally, the simulations are given by using the Robotic Toolbox from MATLAB software to test the derivation. The experiment results are shown that the proposed method is effective.

Robust Nonlinear Control Design for Ionic Polymer Metal Composite based on Sliding Mode Approach
SPEAKER: Aihui Wang

ABSTRACT. In this article, a robust nonlinear tracking control design for ionic polymer metal composite (IPMC) with uncertainties is presented by using particle swarm optimization based sliding mode approach. In detail, for a nonlinear dynamic model with uncertainties, an IPMC artificial muscles position tracking control system based on sliding mode control approach is presented, where, a saturation function is used in the sliding mode control law design to suppress chattering, and the control parameters of sliding mode control are optimized by using particle swarm optimization to obtain quick convergence. The robust stability can be guaranteed. Finally, the effectiveness of the proposed method is confirmed by simulation results.

16:30-18:00 Session 9A: Control Education and Future Prospects
Exploring future directions of Control

ABSTRACT. Control system research is entering a new era, which may be considered a milestone in the history of Systems and Control. The traditional framework of a control system structure – i.e. plant, sensor, actuator and a controller – presents a number of limitations to some current research, i.e. (a) System to be controlled comprise network of subsystems; (b) Control task is achieved by a network of distributed local controllers (agents); (c) New research topics on control of networked behaviour, including consensus, formation and synchronisation, are clearly beyond the scope of the traditional “one controller” framework. It is worth noting that with these new trends some new concepts are emerging, e.g. consensusability, formationability, computability. The intended contributions of this paper are: (1) A new framework of control research represented by a new block diagram and its mathematical treatment. It is pointed out that, many current different studies can be considered as some special cases under this general framework; (2) a brief overview of various research fitting the proposed framework and some open questions. This paper is largely motivated by past, current and future applications of power system control, and is based on a recent invited presentation, of the first author, at a special workshop on “Bridging the Gap – Control Theory and Control Engineering Practice”.

Fuzzy Logic-based Gain Scheduling of Exact FeedForward Linearization Controller for Magnetic Ball Levitation System

ABSTRACT. This paper presents an Exact FeedForward Linearization controller combined with fuzzy-based gain scheduling for single DOF magnetic ball levitation system. The proposed method improves the previously reported techniques in terms of transient response behavior and tracking error. A Luenberger State estimator for the nonlinear/uncertain plant is implemented. Finally, the control law and the estimator are combined and applied experimentally to the magnetic ball levitation system. The results show the effectiveness and the robustness of this scheme regarding the increase of the dynamic range of the tracked signals and the presence of payload variation.

A Survey of Techniques and Opportunities in Power System Automatic Generation Control

ABSTRACT. This paper gives a concise survey of the control methods which have been applied to automatic generation control of power systems. Different control approaches have been categorized and a summary has been given of the context of application and strengths and weaknesses. Such a summary is an effective starting point for determining where future control research is likely to bring the most benefit to the emerging large scale and interconnected structures in the power supply market.

Using clickers in lectures to help identify and teach the control topics students find difficult

ABSTRACT. It is important that academic staff have a good awareness of the preparedness of their classes for new learning. This papers shows how clicker technology has been used both to help staff learn about student preparedness but also to encourage better engagement with learning of control related topics. Some of the data produced will be of generic interest to the community as it gives hard evidence of what is often suspected anecdotally.

16:30-18:00 Session 9B: Rail Applications of Control
A Model of a Repoint Track Switch for Control
SPEAKER: Nick Wright

ABSTRACT. Track switching provides necessary flexibility to a rail network, allowing vehicles to change routes when necessary. Track switches, however, have historically been prone to failure. To increase asset reliability, a concept for a novel design of switch has been developed which allows multi-channel actuation through a novel actuation and locking mechanism, under a project titled ‘Repoint’. This paper describes a mathematical model of the operation a novel Repoint track switch. The model was derived from a first principles physical analysis of the Repoint concept design. The structure of the model mimics the physical structure of the design. Each physical component has an individual sub-model. The model has been used to estimate the actuator drive requirements for a case study mainline switch installation. It has been found that a Repoint track switch could be run from an existing UK signalling power supply. It is anticipated that this model will be used as the basis for a control system design activity for a technology demonstrator installation currently under construction.

Applications of the inerter in railway vehicle suspensions

ABSTRACT. This paper is a review of currently identified applications of the inerter in railway vehicle suspensions. We survey the current state of research in the field, including main results, discussions and conclusions regarding overall applicability.

Detection and isolation of actuator failure for actively controlled railway wheelsets

ABSTRACT. This paper studies a model-based approach for the condition monitoring of an actively controlled railway system, with a focus on actuator failures to detect and isolate failure modes in such a system. It seeks to establish the necessary basis for fault detection to ensure system reliability in the event of an abnormal change in one of the two actuators. Computer simulation is used to demonstrate the effectiveness of the method.

Towards Self-powered Lateral Active Suspension for Railway Vehicles
SPEAKER: Peng Wang

ABSTRACT. This paper investigates the energy consumption of the lateral secondary active suspension for railway vehicles and studies the conditions for self-powered active suspension control. The influence of the performance index weighting factors to both the ride quality and the energy consumption is discussed based on the linear quadratic regulator (LQR) algorithm. Then the energy balance condition is analyzed. With low energy harvesting restriction, the self-powered condition can be achieved. At last, simulation results are provided to validate the feasibility of the self-powered suspension.

16:30-18:00 Session 9C: Medical Applications of Control
Modelling the Self-Tolerance Mechanisms of T Cells: An Adaptive Sliding Mode Control Approach

ABSTRACT. Failure of the mechanisms of tolerance to self antigen by the immune system causes an autoimmune response. The immune system changes its immunological steady-state according to a switching logic based on a function encompassing the interactions between antigen and T cells. The resultant immune response function is regarded as the controller for the immune system. Synergies with variable structure control are immediately apparent. A sliding mode is investigated on a suitable surface which is a function of the concentration of self antigen and T cells. Both immunological and control engineering constraints have been considered in the design of the controller. The magnitude of the discontinuity is tuned to reduce chattering as well as to represent immunological reality. Robust stability and robust performance is achieved. The healthy state of the immune system is maintained using adaptive sliding mode control to model the self-tolerance mechanisms.

Model of the Glucose-Insulin System of Type-1 Diabetics and Optimization-based Bolus Calculation
SPEAKER: Tilman Utz

ABSTRACT. In this contribution, a mathematical model of the glucose-insulin system in the case of type-1 diabetes is presented. This model and is subsequently used to determine an optimal so-called bolus dosage adapted to the diabetic patient's future behaviour. This model on the one hand is chosen with a level of detail comprising the major part of daily situations. On the other hand, it is still relatively easy to parametrize in order to be usable within a so-called bolus calculator. The validity of the model is shown using real patient measurement data and the bolus optimization is carried out in a simulation environment.

Repetitive Control Based Tremor Suppression using Electrical Stimulation

ABSTRACT. Tremor is a common, debilitating movement disorder commonly occurring in neurological disorders, with invasive and pharmacological treatment methods often ineffective. Functional electrical stimulation (FES) holds potential for tremor suppression, but previous control methods have proven of limited success. This paper establishes the feasibility of using repetitive control, a framework which is able to eliminate the effect of periodic disturbances by including an internal model of the oscillation within the control structure. A model of the wrist is developed and two different repetitive control algorithms are applied to suppress tremor via stimulation of wrist flexors and extensors. Experimental results are compared with filter-based methods to establish efficacy of the proposed approach.

Phase-lead ILC based electrode array stimulation using reduced input subspace

ABSTRACT. An iterative learning control (ILC) approach is developed for electrode array based functional electrical stimulation. Building on the `phase-lead ILC' form that has proved clinically effective with single electrodes, the first principled extension to multivariable systems is undertaken, resulting in a set of update laws which require minimal plant information that can be identified in a short initial steady-state test procedure. To further reduce the amount of model information required, a reduced input subspace is embedded in the ILC update. Experimental results using a 24 element electrode array confirm efficacy of the proposed approach for clinical practice.

16:30-18:00 Session 9D: Applied Control
Chair: Paul King
Sliding-Mode Control of an Underactuated Oilwell Drill-String with Parametric Uncertainty

ABSTRACT. The stick-slip oscillation of a multibody drill-string is studied in this paper from the point of view of control of underactuated system using a lumped-parameter model. The model has one control input acting on the rotary table from the land surface and multi-degree-of-freedom downhole parts comprising a series of hollow drill pipes, a number of much stiffer drill collars, and a drill bit suffering highly nonlinear friction to be controlled. Two sliding-mode controllers are studied to suppress the stick-slip oscillation while track a desired rotary speed for the drill-string with estimated physical parameters. The stabilities of the proposed control methods are proved by using the Lyapunov direct method. Extensive simulation results are shown to demonstrate their validity and robustness to parameter variations, disturbances, and measurement noises.

Real-time measurement of ring-rolling geometry using low-cost hardware

ABSTRACT. Ring-rolling is an industrial forming process to produce high-strength metal rings up to 6m diameter. Thick-walled cylindrical workpieces of material, typically metallic alloys, are compressed between two or more internal and external rollers and rotated until a target geometry, often outer diameter, is achieved. The process is inherently unstable and the process is often constrained and/or controlled to improve its stability. This paper presents an image processing algorithm for the measurement of ring geometry through photogrammetry in real-time. These measurements will form part of the feedback control system for a ring-rolling process. An off-the-shelf USB webcam is used to capture images of the ring during forming and the scene is controlled to maximise contrast and minimise occlusions of the ring. The image processing tasks include object identification, edge detection, outlier rejection and distortion rectification. The process has been implemented on a desktop-scale forming machine and has been shown to work at rates suitable for control the ring-rolling process using feedback.

Exact Linearization by Feedback of State Dependent Parameter Models Applied to a Mechatronics Demonstrator

ABSTRACT. The paper develops an exact linearization by feedback approach for State Dependent Parameter (SDP), Proportional-Integral-Plus (PIP) control. The method is demonstrated using a simple automated belt driven by a DC motor equipped with a single board Reconfigurable Input-Output (sbRIO-9631) card, within a Field Programmable Gate Array (FPGA), and with a real time processor for control. The demonstrator is first modeled using a discrete-time SDP model structure, in which the parameters are functionally dependent on measured system states. An exact linearization step returns a linear model with unity coefficients, which is subsequently used to design a PIP control algorithm based on linear system design strategies, including pole assignment and optimal linear quadratic design. Preliminary experimental results demonstrate that the new approach yields an acceptable control performance for the nonlinear system.

Kinetic Modelling of an Industrial Semi-batch Alkoxylation Reactor for Control Studies
SPEAKER: Marcus Nohr

ABSTRACT. Abstract—Semi-batch processes are gaining further importance in the chemical industry, due to the trend to produce more speciality products with higher margins. Besides a constantly high product quality, a maximum space-time-yield is a principal goal of process control for semi-batch processes. This requires to drive the process along its limitations, which often is impossible with standard PID control schemes. More sophisticated control methodologies potentially allow for a maximisation of the spacetime- yield while keeping the product quality high. However the scientific development and test of such methodologies is often conducted using very simplified reactor models, which may allow for a demonstration of the basic feasibility but neglect additional effects, which hamper the transfer to industrial processes. Therefore a more detailed model of a semi-batch process, suitable for the development and test of control schemes is presented in this contribution. Using this model, a simulation study elucidates the limitations of classical temperature control concepts when aiming for a maximisation of the space-time-yield.

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