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Control Theory and Applications, IEE Proceedings -

Issue 3 • Date May 1994

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Displaying Results 1 - 10 of 10
  • Robust control design via eigenstructure assignment, genetic algorithms and gradient-based optimisation

    Page(s): 202 - 208
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (376 KB)  

    The paper presents a new approach for robust control design of multivariable systems via eigenstructure assignment, genetic algorithms and gradient-based optimisation. It takes the combination of the sensitivity and the complementary sensitivity functions of the closed-loop system as the robust control performance index. The gradient calculation of the performance index is described in detail for the closed-loop system with real and complex eigenvalues. The paper makes full use of the freedom provided by eigenstructure assignment to find a controller which stabilises the closed-loop system and minimises the performance index via the combination of genetic algorithms and gradient-based optimisation. The simulation results for the design of a lateral flight control system provide a tutorial demonstration of the power of the method View full abstract»

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  • Adaptive control of discrete-time nonlinear systems using recurrent neural networks

    Page(s): 169 - 176
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    A learning and adaptive control scheme for a general class of unknown MIMO discrete-time nonlinear systems using multilayered recurrent neural networks (MRNNs) is presented. A novel MRNN structure is proposed to approximate the unknown nonlinear input-output relationship, using a dynamic back propagation (DBP) learning algorithm. Based on the dynamic neural model, an extension of the concept of the input-output linearisation of discrete-time nonlinear systems is used to synthesise a control technique for model reference control purposes. A dynamic learning control architecture is developed with simultaneous online identification and control. The potentials of the proposed methods are demonstrated by simulation studies View full abstract»

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  • Simultaneous robust stabilisation of two normalised coprime factor plant balls

    Page(s): 191 - 196
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (340 KB)  

    The problem treated concerns the design of a single controller which simultaneously stabilises two nonconcentric balls of single-input/single-output plants. This is done by using the normalised left coprime factor plant description with H-bounded uncertainty to characterise each plant ball. Necessary conditions for being able to solve this problem are developed and used to provide a computational approach for determining a controller. Several examples are given to demonstrate the validity of the necessary conditions and the controller synthesis procedure View full abstract»

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  • Kernels of anticausal operators and the multivariable generalised predictive control problem

    Page(s): 181 - 190
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (672 KB)  

    Eigenvector or principal direction projections provide a convenient means of decomposing the multivariable problem into a set of scalar control problems, each of which can be solved using single-input single-output generalised predictive control. However the bicausal nature of eigenvector or principal direction representations leads to anticausality difficulties which in the past have been overcome by a `forward' shift in the control horizon. Under some circumstances this shift introduces an undesirable pseudo-delay, and a previous paper proposed the use of `kernels' of bicausal operators as an effective remedy for the scalar case. In the paper the authors explore the relationship between these kernels and scaling of the bicausal representations and propose algorithms which overcome the pseudo-delay problems in the multivariable case View full abstract»

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  • Necessary conditions for limit cycles in multiloop relay systems

    Page(s): 163 - 168
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (388 KB)  

    The paper examines the behaviour of multivariable systems under multiloop relay feedback control. The analysis is a generalisation of the Tsypkin method (1984) for the prediction of forced oscillations in single variable systems. It is exact in the sense that a complete harmonic balance is considered in all the loops. The results are valid for systems with characteristic loci with phase lags more than 180°. It is shown that such multivariable systems under multiloop relay feedback may exhibit limit cycle oscillations in three possible modes. The first mode consists of identical relay outputs which are square waves with precisely one fundamental frequency. The second mode is characterised by relay outputs which are square waves of different fundamental frequencies in each loop. In this mode, each loop behaves like a single variable system oscillating at a unique limit cycle frequency. The third mode is one of periodic complex oscillations consisting of multiple relay switches within one fundamental period. The necessary conditions derived show that the modes are related to the strength of the interactions in the respective loops. The authors derive a graphical technique to determine when unique oscillations (with distinct frequencies) at the output of each relay may occur and when single frequency or complex oscillations may exist instead. Simulation results are given to illustrate the possible scenarios View full abstract»

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  • Numerical robustness and efficiency of generalised predictive control algorithms with guaranteed stability

    Page(s): 154 - 162
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (556 KB)  

    Three recent publications proposed modifications to the generalised predictive control algorithm which guarantee closed-loop stability. Of these the first two adopt the same philosophy, namely that of constrained receding horizon predictive control (CRHPC), whereas the third adopts a stable generalised predictive control (SGPC) strategy by first stabilising then controlling the plant. The purpose of the paper is to examine the relationship between CRHPC and SGPC. It is shown that, theoretically, the two approaches are equivalent, but is is also shown that CRHPC could be subject to significant numerical instability problems. Two alternative improved implementations of CRHPC are proposed, but SGPC is shown to have the advantage in terms of numerical stability and computational efficiency View full abstract»

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  • New robust model reference adaptive control algorithm

    Page(s): 177 - 180
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (232 KB)  

    A new robust model reference adaptive control scheme is proposed to achieve robustness to bounded disturbance. A key feature of this scheme is that the knowledge of neither the upper bound on the disturbance nor the upper bound on the norm of the matching controller parameters is required. Another advantage of the scheme is its zero output error tracking View full abstract»

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  • Near time-optimal control of nonlinear servomechanisms

    Page(s): 145 - 153
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (456 KB)  

    Time-optimal control of a servomechanism requires a nonlinear control law based on a switching function. The switching function depends on the characteristics of the actuator and on the load. In practical servomechanisms the friction load may be unknown and may slowly vary. In such cases the optimal switching function is unknown prior to the start of each move. A controller is developed which estimates the optimal switching function during each move, thus enabling near time-optimal control to be achieved. The controller allows for certain nonlinearities in the actuator and in the friction/velocity function, and avoids the problems of chattering and limit cycling normally associated with time-optimal control. Experimental results are presented View full abstract»

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  • Observing a subset of the states of linear systems

    Page(s): 137 - 144
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    A selective state observer capable of asymptotically tracking any arbitrarily chosen subset of the state vector of linear time-invariant multivariable dynamic systems is introduced. The dynamics of the observer are derived from a model of the subset to be estimated. It is shown that the only condition for the asymptotic tracking of the subset is that the derived model be observable. A simple and systematic observer design method is presented and numerical examples are given to illustrate the properties of the new observer and its design method View full abstract»

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  • Decoupling design of multivariable generalised predictive control

    Page(s): 197 - 201
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (276 KB)  

    For many multivariable systems, because of the strong cross coupling between controlled variables, it is important to design the decoupling controller. The paper presents a decoupling design of multivariable generalised predictive control by combining feedforward control with multivariable generalised predictive control, which can realise decoupling control for systems with arbitrary time delay structure View full abstract»

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