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Control Theory and Applications, IEE Proceedings -

Issue 5 • Date Sep 1998

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Displaying Results 1 - 13 of 13
  • LQG controllers for discrete-time multivariable systems with different transport delays in signal channels

    Page(s): 449 - 462
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1060 KB)  

    The design of stochastic LQG optimal tracking and regulating systems is considered for discrete-time systems with different time delays in different signal channels. A Wiener frequency domain solution for the closed-loop optimal controller is first obtained in the z-domain. This solution is physically realisable but involves the transport-delay operator. A state-space version of the controller is then derived from the frequency domain results. It is shown that the state equation based controller includes a Kalman predictor and state-estimate feedback. This confirms that a form of the separation principle holds for linear systems containing different transport delays on input and output signal channels. The Wiener solution applies to multivariable systems that may be unstable, nonminimum phase and nonsquare. The process and measuring system noise terms may be correlated and be coloured or white. It is shown that for certain classes of system the optimal controller can be implemented using a combination of finite dimensional and pure transport delay elements. The main advantage is that the estimator is of much lower order than the traditional solution. The gain computation involves a reduced state equal to that of the delay free system and is thereby independent of the length of the delay. The state-space form of the optimal controller may be implemented using either a finite impulse-response block, or alternatively in a Smith predictor form. In this latter case it has the same limitation, namely the plant must be open-loop stable. This restriction does not apply to either the Wiener or finite impulse response state space solutions View full abstract»

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  • Nonlinear robust controller for a class of nonlinear uncertain systems

    Page(s): 405 - 410
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    The authors present an alternative control design approach for nonlinear uncertain systems that do not satisfy the generalised matching conditions. The control design scheme is a combination of the backstepping design technique, along with a dynamic recursive control design. The controller yields global stability of uniform ultimate boundedness, and requires only the knowledge of the bounding function of the uncertainty along with the system states. The form of the controller is a nonlinear nonhomogenous ordinary differential equation where its solution yields the control to be injected into the system model. This unique feature is recursively structured so that the control is generated in real time as the system solution is computed. The control design is applied to an air breathing tail controlled vehicle model to demonstrate the applicability of the control design to real world systems View full abstract»

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  • Efficient numerical method for the discrete-time symmetric matrix polynomial equation

    Page(s): 443 - 448
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    A numerical procedure is proposed to solve a matrix polynomial equation frequently encountered in discrete-time control and signal processing. The algorithm is based on a simple rewriting of the original equation in terms of a reduced Sylvester matrix. In contrast to previously published methods, it does not make use of elementary polynomial operations. Moreover, and most notably, it is numerically reliable. Basic examples borrowed from control and signal processing literature are aimed at illustrating the simplicity and efficiency of this new numerical method View full abstract»

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  • Autotuning gain parameter implementation with fuzzy learning control scheme for DC brushless servo system

    Page(s): 419 - 427
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (672 KB)  

    Deals with an advanced control method of system gain parameter autotuning implementation for a DC brushless servo drive system. Which is based on a fuzzy reasoning logic with an automatically processed learning control strategy. In the learning operation, fuzzy rules are generated automatically so as to be suitable for unknown mechanical load which is linked to a servo motor shaft and memorised in a database. As a result, the performance in the gain parameter autotuning scheme is improved in accordance with increasing the number of learning operations. The feasibility effectiveness of the practical application for this autotuning procedure in DC brushless servo drive systems is confirmed on the basis of experimental results View full abstract»

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  • Design of optimal reduced order filter for unstable discrete time systems

    Page(s): 397 - 404
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (648 KB)  

    The paper is concerned with H2 optimal reduced-order filtering for a linear discrete time signal model. The signal model is allowed to be unstable. The objective is to obtain a reduced-order filter that not only gives rise to a stable filtering error transfer function but also minimises the H2 norm. The authors first derive a parameterisation of a set of filters of fixed order which lead to stable filtering error transfer functions. Such a parameterisation is given in terms of an arbitrary orthogonal projection matrix. As a consequence, the problem of minimising the H2 norm of the filtering error transfer function over the set of reduced-order filters is formulated as an equivalent unconstrained parametric optimisation problem over a compact manifold. Two gradient-based algorithms are then proposed to compute an optimal reduced-order filter. The good properties of the algorithms, including the convergence property, are established theoretically as well as demonstrated numerically with an example View full abstract»

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  • Double-controller scheme for control of processes with dominant delay

    Page(s): 479 - 484
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (560 KB)  

    A double-controller structure is proposed for control of processes with dominant time delay. In contrast to the Smith predictor, the proposed control scheme contains two controllers, a set point controller and a load controller, and a process model. With this structure, the setpoint and load responses of the closed-loop system are no longer coupled, and the two controllers can be separately designed to obtain good performance in both setpoint tracking and load rejections. Any errors resulting from the inevitable mismatch between the model and the process can be viewed as additional load disturbances, and are compensated by the load controller. The load controller is tuned to be insensitive to the model structure and parameters, to accommodate large model uncertainty, for which the standard Smith predictor may give poor regulatory performance and even fail to work. Extensive simulations show that the proposed scheme is superior to the Smith predictor in the presence of large uncertainty in process dynamics View full abstract»

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  • PID tuning for unstable processes based on gain and phase-margin specifications

    Page(s): 392 - 396
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    PID control is widely used to control stable processes, however. PID control for unstable processes is less common. In the paper, simple formulas are derived to tune the PID controller for unstable processes to meet gain and phase margin specifications. The stability of the closed-loop system is ensured by the Nyquist stability criterion. These formulas are derived for first- and second-order processes with time delay. Simulation results are given to show the accuracy of the formulas and the performance that can be achieved View full abstract»

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  • Design of a hydraulic force control system using a generalised predictive control algorithm

    Page(s): 428 - 436
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (776 KB)  

    Reports the development of a hydraulic force control system utilising a generalised predictive control (GPC) technique. Varying dynamics of the moving actuator due to variable payload or environmental stiffness, as well as changes in the characteristics of hydraulic components, make the dynamics of hydraulic servosystems conceptually time varying. This allows the application of adaptive controls as an attractive solution. A suitable model of actuator environment is established and the recursive U-D factorisation technique is adopted for online estimation of time varying model parameters. Various step and tracking experiments are performed on a laboratory electrohydraulic actuator test stand to demonstrate good performance and the promise of the developed force control system. In spite of poor dynamics and high nonlinearities (control voltage saturation, fluid flow deadband and dry friction in the hydraulic actuator) successful control tests are performed repetitively View full abstract»

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  • Towards the formalisation of soft systems models using Petri net theory

    Page(s): 463 - 471
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (848 KB)  

    The analytical capability of conceptual models that are used in a soft systems methodology to capture the processes within a business organisation is examined and extended. Specifically, the models known as systemigrams, which form part of the Boardman soft systems methodology, are considered. The informal nature of systemigrams allows a nonspecialist to easily create models of processes, but it does not permit analysis of the resulting model. Hence, problems can occur in verifying the correctness of these models. This problem is addressed by presenting a translation algorithm that converts systemigram descriptions into Petri net models. This translation allows the behaviour, represented by the systemigram. To be analysed via Petri net theory, and it has the potential of performing what if analysis. Application of this algorithm is shown via a case study that translates and analyses a systemigram of a realistic industrial process that forms the order intake phase of a product's life cycle View full abstract»

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  • Constrained multivariable cautious stable predictive control

    Page(s): 385 - 391
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (436 KB)  

    The characterisation of the class of stable predictions has been used to derive single-input single-output model based predictive control laws with guaranteed stability. Here it is shown that this work can be extended to the multivariable case View full abstract»

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  • Autogeneration of fuzzy rules and membership functions for fuzzy modelling using rough set theory

    Page(s): 437 - 442
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (752 KB)  

    Rough set theory can represent a degree of consistency between condition and decision attributes of data pairs which do not have linguistic information. By using this ability, a measure called occupancy degree is defined: which can represent the degree of consistency between premise and consequent variables in fuzzy rules describing given experimental data pairs. A method is also proposed by which the projected data is partitioned on the input space, and an optimal fuzzy rule table and membership functions of input and output variables are found from data without preliminary linguistic information. The validity of the proposed method is examined by modelling data pairs which are randomly generated from a fuzzy system View full abstract»

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  • Analysis of sensitivity measures of finite-precision digital controller structures with closed-loop stability bounds

    Page(s): 472 - 478
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (656 KB)  

    The problem of digital controller structures and the effect of finite-word-length (FWL) implementation on the closed-loop stability of digital feedback control systems is addressed. A framework is presented to derive two lower stability bounds for a closed-loop system, which are controller structure dependent, and then to solve the optimal FWL controller structure problem by maximising one of these lower bounds. This yields an improved method to design optimal finite-precision controller structures with better numerical accuracy and closed-loop stability characteristics. Comparisons using numerical examples from two digital controller structures demonstrate that the procedure proposed for the more efficient measure yields an improved finite controller realisation with combined lower bits and higher lower stability bounds View full abstract»

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  • Design of a sliding mode controller with fuzzy sliding surfaces

    Page(s): 411 - 418
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (472 KB)  

    The authors suggest a sliding mode controller, using a linear time-varying sliding surface instead of the fixed sliding surface, which has robustness against parameter variations and extraneous disturbances during the reaching phase to the final sliding surface. By applying the Takagi-Sugeno (TS) fuzzy algorithm to the regulation of the linear time-varying sliding surface: the reaching time of the system trajectory is shorter than in the fixed method. This proposed scheme has better performance than the conventional method in reaching time, parameter variation and extraneous disturbance. To demonstrate its performance, the proposed control algorithm is applied to a rotational inverted pendulum View full abstract»

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