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IEE Proceedings - Control Theory and Applications

Issue 5 • Date Sep 1994

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Displaying Results 1 - 10 of 10
  • Robust stabilisation for a class of time-delay nonlinear systems

    Publication Year: 1994, Page(s):285 - 288
    Cited by:  Papers (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (232 KB)

    The authors examine the problem of robust stabilisation for a class of time varying delay systems with both Lipschitz and non-Lipschitz bounded uncertainties. The non-Lipschitz bounded uncertainty is assumed to satisfy a matching condition but the Lipschitz bounded one may not. A Riccati approach is used to design a memoryless state feedback controller, which assures global exponential stability o... View full abstract»

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  • Adaptive optimum start-up and shut-down time controllers for heating systems based on a robust gradient method

    Publication Year: 1994, Page(s):323 - 328
    Cited by:  Patents (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (324 KB)

    The paper presents an adaptive optimum start-up time controller and an adaptive optimum shut-down time controller for heating systems based on a robust gradient method. Using very simple models of the heating and cooling processes, it is concluded that for each controller only one parameter is necessary to identify the correct values of the preheat and shut-down time. A robust gradient method is a... View full abstract»

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  • Block partial derivative and its application to neural-net-based direct model-reference adaptive control

    Publication Year: 1994, Page(s):305 - 314
    Cited by:  Papers (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (512 KB)

    The concept of block partial derivative and the associated algebra are introduced. The algebra is then applied to direct-model-reference adaptive control (MRAC) of discrete-time nonlinear plants. Three MRAC algorithms are developed employing identification of the forward model, extended MIT rule and extended SPR rule. Local-convergence properties and results of simulation study are presented View full abstract»

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  • Stabilising properties of constrained predictive control

    Publication Year: 1994, Page(s):295 - 304
    Cited by:  Papers (9)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (680 KB)

    Standard generalised predictive control (GPC) and constrained receding-horizon predictive control (CRHPC) stability results have traditionally been derived in the state-space, using the properties of the solution of the Riccati equation associated with the control law. Unfortunately this type of study does not readily extend to constrained control laws which are nonlinear. By invoking the monotoni... View full abstract»

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  • Mixed H optimisation with model-matching

    Publication Year: 1994, Page(s):329 - 340
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (708 KB)

    This paper describes a class of the mixed H optimisation with model-matching problems. The sensitivity and stability margin objectives are integrated in the model-matching design, respectively. Both approaches give a means of directly accessing the sensitivity/robustness objectives through a trade-off on the perfect model-matching objective. These applications to the known H... View full abstract»

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  • Neural-net controller for nonlinear plants: design approach through linearisation

    Publication Year: 1994, Page(s):315 - 322
    Cited by:  Papers (12)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (524 KB)

    A three-stage procedure for design of a neural-net controller for nonlinear plants is developed. The design is based on linearisation of the plant at each operating point. First, the input-output data of the plant is used to train a neural-net model of the plant. Next, the plant is controlled using a time-varying linear controller based on the linearised plant model at each operating point. The ne... View full abstract»

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  • Closed-form solution of the continuous-time Lyapunov matrix equation

    Publication Year: 1994, Page(s):350 - 356
    Cited by:  Papers (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (332 KB)

    A simple algorithm is proposed for a closed-form solution to the continuous-time Lyapunov matrix equation using the Routh array, which is useful for the computation of controllability, observability and cross-Gramians for both SISO and MIMO systems. The proposed algorithm provides the Gramians directly from the Routh array and thus is more efficient than existing algorithms. The closed-form soluti... View full abstract»

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  • Robust trajectory tracking for flexible piezoelectric structures

    Publication Year: 1994, Page(s):289 - 294
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (368 KB)

    The robust trajectory tracking problem is stated and solved for a thin planar sandwich structure, consisting of two piezoelectric films, mounted on an elastic support. The proposed controller asymptotically stabilises the structure, and guarantees for the generalised coordinates, which are introduced to approximately describe the shape of the structure, an arbitrarily bounded steady-state tracking... View full abstract»

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  • Adaptive neural-network-based approach for the control of continuously stirred tank reactor

    Publication Year: 1994, Page(s):341 - 349
    Cited by:  Papers (3)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (640 KB)

    An online adaptive neural-network-based controller (OANNC) is developed in the paper. The detailed design procedures of the OANNC are given, along with an illustrative example of controlling a continuously stirred tank reactor. Simulation results show that the OANNC is successful in controlling nonlinear time-varying systems with slow dynamics. Compared with conventional neural-network controllers... View full abstract»

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  • Linear splines with adaptive mesh sizes for modelling nonlinear dynamic systems

    Publication Year: 1994, Page(s):277 - 284
    Cited by:  Papers (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (468 KB)

    A method of identifying nonlinear dynamic models is presented which exhibits fast convergence, and adapts its memory requirements to cope with the complexity of the problem. The method modifies the CMAC algorithm by replacing fixed weights by linear splines, and may be considered as a single layer neural net. The position and number of knots (points on which the spline weights are centred) are det... View full abstract»

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