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Control (CONTROL), 2012 UKACC International Conference on

Date 3-5 Sept. 2012

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Displaying Results 1 - 25 of 196
  • Author index

    Page(s): A-1 - A-10
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  • [Title pages]

    Page(s): i - ii
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  • Organising institutions

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  • Table of contents

    Page(s): xii - xxi
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  • Tensegrity-based formation control of unmanned vehicles

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1633 KB) |  | HTML iconHTML  

    A new formation control methodology modelled by a virtual tendon-driven system using the tensegrity structures is presented. The objective of the work is to regulate the formation of unmanned vehicles within the communications bandwidth and perform point-to-point manoeuvring tasks. The reaction control forces that are experienced by vehicles in the formation are determined by the admissible tendon forces in tensegrity. A control law is designed to stabilize the interspacing between the vehicles in the presence of disturbances by making the combined use of string and spring characteristics. Simulation results demonstrate the effectiveness of the proposed approach in terms of maintaining the formation and avoiding inter-vehicle collisions. Formation shape changing is also performed by varying the relative parameters between the vehicles. View full abstract»

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  • Polymer extrusion process monitoring using nonlinear dynamic model-based PCA

    Page(s): 7 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1098 KB)  

    Polymer extrusion is one of the final forming stages in the production of many polymeric products in a variety of applications. It is also an intermediate processing step in injection moulded, blown film, thermo-formed, and blow moulded products. However, polymer extrusion is a complex process which is difficult to set up, monitor, and control. As a consequence, high levels of off- specification products and long down-times are the problems facing the plastics industry. This paper proposes a new method for fault detection of the polymer extrusion processes, where the nonlinear finite impulse response (NFIR) model and principal component analysis (PCA) are integrated to form a nonlinear dynamic model-based PCA monitoring scheme. Here the NFIR model is used to capture the nonlinearity and dynamics of the extrusion process. The residuals resulting from the difference between the model predicted outputs and process outputs are then analyzed by PCA to detect process faults. The experimental results confirm the efficacy of the proposed model-based PCA approach for fault detection of polymer extrusion processes. View full abstract»

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  • A new bandwidth scheduling method for networked learning control

    Page(s): 13 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1022 KB) |  | HTML iconHTML  

    In this paper, the optimal bandwidth allocation scheduling problem for two-layer networked learning control systems (NLCSs) is studied. In NLCS, multiple networked feedback control loops share a common communication channel and they compete to bid for available bandwidth. A non-cooperative game fairness model is first formulated, which takes into consideration of a number of factors, such as transmission data rate, control sampling strategy and scheduling pattern. Then, a novel two-layer hierarchical market competition algorithm (THMCA) is proposed. Two hierarchical population individuals are defined in the algorithm, namely the holding companies and the subsidiary companies which altogether form conglomerates. Market competitions among these conglomerates lead to the convergence to a monopoly at the end, resulting in an optimal solution of the above problem. The algorithm is shown to have a high convergence rate and the comparison simulation results on a NLCS with up to 100 subsystems have demonstrated the effectiveness of the proposed method. View full abstract»

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  • An improved conjugate gradient algorithm for radial basis function (RBF) networks modelling

    Page(s): 19 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (394 KB) |  | HTML iconHTML  

    This paper proposes a new nonlinear optimization algorithm for the construction of radial basis function (RBF) networks in modelling nonlinear systems. The main objective is to speed up the learning convergence of the conventional conjugate gradient method. All the hidden layer parameters of RBF networks are simultaneously optimized by the conjugate gradient method while the output weights are adjusted accordingly using the orthogonal least squares (OLS) method. The derivatives used in the conjugate gradient algorithm are efficiently computed using a recursive sum squared error criterion. Numerical examples show that the new method converges faster than the previously proposed continuous forward algorithm (CFA). View full abstract»

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  • Heuristically optimized RBF neural model for the control of section weights in stretch blow moulding

    Page(s): 24 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (497 KB) |  | HTML iconHTML  

    The injection stretch-blow Moulding (ISBM) process is typically used to manufacture PET containers for the beverage and consumer goods industry. The process is somehow complex and users often have to heavily rely on trial and error methods to setup and control it. In this paper, a novel identification method based on a radial basis function (RBF) network model and heuristic optimization methods, such as particle swarm optimization (PSO), deferential evolution (DE), and extreme learning machine (ELM) is proposed for the modelling and control of bottle section weights. The main advantage of the proposed method is that the non-linear parameters are optimized in a continuous space while the hidden nodes are selected one by one in a discrete space using a two-stage selection algorithm. The computational complexity is significantly reduced due to a recursive updating mechanism. Experimental results on simulation data from ABAQUS are presented to confirm the superiority of the proposed method. View full abstract»

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  • How to reduce congestion on TCP/AQM networks with simple adaptive PID controllers

    Page(s): 30 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1076 KB) |  | HTML iconHTML  

    Congestion is a problem in real networks. Users do not want to lose information and data should be delivered as fast and reliably as possible. This is really difficult to achieve. Moreover, networks work in changing environments: number of users, type of traffic, delays in transmission, etc. So this paper presents how to design PID controllers that take network changes into account. Non-linear simulations using ns-2 will show the goodness of the approach when compared with classical PID, drop tail and RED. View full abstract»

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  • Robust adaptive actuator failure compensation controller for systems with unknown time-varying state delays

    Page(s): 36 - 41
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (631 KB) |  | HTML iconHTML  

    An output feedback model reference adaptive controller is developed for a class of linear systems with multiple unknown time-varying state delays and in the presence of actuator failures. The adaptive controller is designed based on SPR-Lyapunov approach and is robust with respect to multiple unknown time-varying plant delays and to an external disturbance with unknown bounds. Closed-loop system stability and asymptotic output tracking are proved using suitable Lyapunov-Krasovskii functional and Simulation results are provided to demonstrate the effectiveness of the proposed controller. View full abstract»

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  • Invariant control of non-linear elements in a stacked High Redundancy Actuator

    Page(s): 42 - 47
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (718 KB) |  | HTML iconHTML  

    The High Redundancy Actuator (HRA) concept aims to provide a single actuator comprising many cooperating actuation elements. The potential benefits of this include improved overall reliability, availability, and reduced need for oversizing of actuators in safety critical applications. This paper deals with the question of distributing the load evenly between a stack of elements despite non-linear characteristics. View full abstract»

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  • Control of chaotic systems with uncertain parameters and stochastic disturbance by LMPC

    Page(s): 48 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (929 KB) |  | HTML iconHTML  

    For the chaotic systems with uncertain parameters and stochastic disturbance, in order to satisfy some optimal performance index when chaos control is achieved, the Lyapunov-based model predictive control (LMPC) is introduced. The LMPC scheme is concerned with an auxiliary controller which is constructed in advance. Based on the auxiliary controller and stochastic stability theory, it is shown that the chaotic systems with uncertain parameters and stochastic disturbance are practical stable. With the help of the auxiliary controller, the stability of LMPC can be guaranteed as well as some optimality property. As an example, the unified chaotic system with uncertain parameter and stochastic disturbance is considered and simulation results show the effectiveness of the proposed method. View full abstract»

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  • Hybrid geno-fuzzy controller for seismic vibration control

    Page(s): 52 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (734 KB) |  | HTML iconHTML  

    This paper evaluates the possibility of applying a geno-fuzzy control strategy to a magnetorheological semi-active damper for seismic vibration control. The proposed control strategy is designed and then tested and validated in a simulated environment. The control strategy is validated by considering a more destructive seismic disturbance as input for the damper-structure system. The proposed geno-fuzzy hybrid controller offers improved performance and implementability for real-time applications. View full abstract»

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  • Optimal control scheme for nonlinear systems with saturating actuator using ε-iterative adaptive dynamic programming

    Page(s): 58 - 63
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (755 KB) |  | HTML iconHTML  

    In this paper, a finite-horizon optimal control scheme for a class of nonlinear systems with saturating actuator is proposed by an improved iterative adaptive dynamic programming (ADP) algorithm. The Hamilton-Jacobi-Bellman (HJB) equation corresponding to constrained control is formulated using a suitable nonquadratic function. Then mathematical analysis of the convergence is presented, by proving that the performance index function can reach the optimum using the adaptive iteration. Finally the finite-horizon optimal control law can be obtained by the ε-iterative adaptive algorithm. The examples are given to demonstrate the effectiveness of the above methods. View full abstract»

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  • Active control of speed fluctuations in rotating machines using feedback linearization

    Page(s): 64 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (912 KB) |  | HTML iconHTML  

    This paper presents a method for actively controlling torsional vibrations in rotating machines caused by angle-dependent parameters. The work is motivated by rotating machines with crank or cam gear mechanisms that cause fluctuations in the angular speed when the machine is driven by a constant load torque or when the speed is controlled with conventional controllers. A very general model for such a system is introduced and used to derive a control law by feedback linearization. With this control law, the speed fluctuations are completely eliminated and desired linear dynamics can be prescribed for the system. The method is tested in a simulation study with a model of a real industrial machine. Although the proposed method works well, the study is preliminary in the sense that the method has not been applied experimentally and its robustness has not been assessed. View full abstract»

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  • An adaptive sliding mode approach to decentralized control of uncertain systems

    Page(s): 70 - 75
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1518 KB) |  | HTML iconHTML  

    This paper proposes a systematic adaptive sliding mode controller design for the decentralized system with nonlinear interactions and unmatched uncertainties. An adaptive tuning approach is developed to deal with unknown but bounded uncertainties/interactions. The sliding surface is designed which obviates the use of regular transformation, by solving a simple LMI-based optimization problem. The feasibility of the LMIs is also discussed in this paper. Finally, a numerical example is used to illustrate this method. View full abstract»

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  • A novel decoupling control method for multivariable systems with disturbances

    Page(s): 76 - 80
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (671 KB) |  | HTML iconHTML  

    This paper presents a novel decoupling method for multivariable systems with disturbances. In this method, the undesirable coupling parts in each loop are treated as the output disturbances. These disturbances, as well as the external disturbances, can be actively rejected by the equivalent-input-disturbance (EID) approach. The parameters of the controller in each loop can be designed independent of each other. A typical example demonstrates the simplicity in parameters design and good performance in decoupling control and disturbance rejection. View full abstract»

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  • Robust decentralized control design using integral sliding mode control

    Page(s): 81 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (929 KB)  

    The problem of robust decentralization of uncertain inter-connected systems is concerned with the goal of de-coupling a Lipschitz non-linear systems into individual “decentralized” subsystems satisfying security and fault-tolerance objectives. This work proposes a new strategy for robust decentralized control in which each subsystem uses an observer-based state estimate structure invoking an approach to separation principle recovery, based on Integral Sliding Model Control (ISMC) with careful consideration of both matched and unmatched uncertainties arising from inter-connections and disturbances. The proposed design strategy for the linear observer and uncertainty de-coupling designs involves a single LMI. An example of 3 unstable inter-connected non-linear systems is used to illustrate the power of the approach. View full abstract»

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  • Synthesis of variable gain controllers based on LQ optimal control for a class of uncertain linear systems

    Page(s): 87 - 91
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    This paper proposes a new variable gain controller for a class of uncertain linear systems. The proposed variable gain controller is based on optimal control for the nominal system and consists of the optimal feedback gain and a time-varying adjustable parameter which is designed so as to reduce the effect of uncertainties, i.e. the proposed variable gain controller can achieve good transient performance which is close to LQ optimal control for the nominal system. In this paper, we show sufficient conditions for the existence of the proposed variable gain controller for uncertain linear systems. Finally, numerical examples are presented. View full abstract»

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  • Output regulation for switched linear systems with different coordinate transformations

    Page(s): 92 - 95
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (686 KB) |  | HTML iconHTML  

    This paper addresses the output regulation problem for switched linear systems. When each regulation equation has their own solution, we give a sufficient condition for the output regulation problem to be solvable. Firstly, we give the regulation equations of switched linear systems and the relation of the transformed states between two consecutive switching times. Secondly, the existence of a minimal average dwell-time for every switching sequence is assumed, and by virtue of an appropriate Lyapunov analysis, the output regulation is achieved. Our result is of much less conservativeness. View full abstract»

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  • Design of switching adaptive laws for the state tracking problem

    Page(s): 96 - 101
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (647 KB) |  | HTML iconHTML  

    In this paper, we address the issue of the state tracking control for model reference adaptive control systems. For a given plant with a known structure and unknown parameters, this problem can be solved by designing an adaptive law for traditional model reference adaptive control designs. In this paper, for a plant with finite fixed adaptive laws where none of them guarantees the states of plant track those of the reference model, there are not allowed to design other adaptive law. In this case, we formulate a switching mechanism between these adaptive laws to track the reference model. A sufficient condition is given for the problem to be solvable via the convex combination technique, and a switching law is designed. The theoretical derivations are illustrated by means of an example. View full abstract»

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  • An adaptive observer-based parameter estimation algorithm with application to road gradient and vehicle's mass estimation

    Page(s): 102 - 107
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (770 KB) |  | HTML iconHTML  

    A novel observer-based parameter estimation algorithm with sliding mode term has been developed to estimate the road gradient and vehicle weight using only the vehicle's velocity and the driving torque from the engine. The estimation algorithm exploits all known terms in the system dynamics and a low pass filtered representation to derive an explicit expression of the parameter estimation error without measuring the acceleration. The proposed algorithm which features a sliding-mode term to ensure the fast and robust convergence of the estimation in the presence of persistent excitation is augmented to an adaptive observer and analyzed using Lyapunov Theory. The analytical results show that the algorithm is stable and ensures finite-time error convergence to a bounded error even in the presence of disturbances. A simple practical method for validating persistent excitation is provided using the new theoretical approach to estimation. This is validated by the practical implementation of the algorithm on a small-scaled vehicle, emulating a car system. The slope gradient as well as the vehicle's mass/weight are estimated online. The algorithm shows a significant improvement over a previous result. View full abstract»

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  • Experimental study of a capsubot for two dimensional movements

    Page(s): 108 - 113
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1634 KB) |  | HTML iconHTML  

    A capsubot (capsule robot) which works on the principle of internal reaction force has no external moving parts whereas a conventional robot has legs and/or wheels. It is an underactuated mechanical system and has a lot of potential applications such as medical diagnosis, underground pipe leakage detection, rescue work in the hazardous environment etc. However, most capsule robots studied/developed can only move in one dimension (1D). This paper presents the implementation of the recently proposed double parallel mass capsubot which uses two parallel inner masses (IMs) to move the capsubot in two dimensions (2D). A three stage control strategy is proposed to resolve the control issue of underactuated mechanical system. A closed-loop control approach is applied to the IMs of the capsubot. The comparison with the simulation studies are also obtained and analyzed. View full abstract»

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  • Wind turbine sensor fault tolerant control via a multiple-model approach

    Page(s): 114 - 119
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1266 KB) |  | HTML iconHTML  

    This paper presents a new strategy for wind turbine fault tolerant control (FTC) to optimise the wind energy captured by a wind turbine operating at low wind speeds. The FTC strategy uses Takagi-Sugeno (T-S) fuzzy observers with state feedback control to maintain nominal wind turbine control without changes in both the fault and fault-free cases. The proposed strategy obviates the need for sensor fault residual evaluation and observer switching by using a fuzzy proportional multiple integral observer (PMIO) to mask i.e. `implicitly compensate' the sensor fault(s) from the controller input and provide good estimation over a wide range of sensor fault scenarios. The proposed FTC method is applied to a 5 MW offshore wind turbine (OWT) benchmark model. View full abstract»

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