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1887

IEE Proceedings D (Control Theory and Applications)

Volume 140, Issue 6, November 1993

Volumes & issues:

Volume 140, Issue 6

November 1993

Generalised command matching for a robot gripping an inertial load
State space based adaptive control with pole restriction
  • Author(s): M.S. Ahmed
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 380 –392
  • DOI:  10.1049/ip-d.1993.0050
  • Type: Article
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  • p. 380 –392 (13)
    A state space based self-tuning controller is proposed that incorporates a closed loop pole restriction principle. The plant matrices, Kalman gain and the states are estimated using a bootstrap method. The state feedback control design is based upon a modified LQ infinite-time control that restricts the closed loop poles within a user-specified disk in the z-plane to meet the maximum overshoot and the maximum settling time specifications. The control design is called only when the estimated closed loop poles with the fixed existing control rule move out of the specified disk. This approach reduces the computational requirement significantly and also increases the stability robustness by providing a piecewise time-invariant control.
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Direct adaptive output tracking control using multilayered neural networks
  • Author(s): L. Jin ; P.N. Nikiforuk ; M.M. Gupta
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 393 –398
  • DOI:  10.1049/ip-d.1993.0051
  • Type: Article
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  • p. 393 –398 (6)
    Multilayered neural networks are used to construct nonlinear learning control systems for a class of unknown nonlinear systems in a canonical form. An adaptive output tracking architecture is proposed using the outputs of the two three-layered neutral networks which are trained to approximate the unknown nonlinear plant to any desired degree of accuracy by using the modified back-propagation technique. A weight-learning algorithm is presented using the gradient descent method with a dead-zone function, and the descent and convergence of the error index during weight learning are shown. The closed-loop system is proved to be stable, with the output tracking error converging to the neighbourhood of the origin. The effectiveness of the proposed control scheme is illustrated through simulations.
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Self-tuning control using the right-matrix-fraction innovation description
Intelligent supervision of servo control
  • Author(s): M.H. Perng  and  H.H. Chang
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 405 –412
  • DOI:  10.1049/ip-d.1993.0053
  • Type: Article
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  • p. 405 –412 (8)
    In this paper two types of intelligence supervised controllers are proposed with the aim to achieve an overall performance beyond the limit of linear controllers. In each case, the overall controller has a hierarchical structure with two conventional linear controllers in the bottom layer to perform accurate control action under the supervision of a reasoning process in the top layer. The reasoning process consists of heuristic rules drawn from our physical insight, and can easily be implemented either by fuzzy logics or by IF … THEN statements. Both intelligence supervised controllers achieve a performance beyond the limit of linear control laws, and are superior to both a fuzzy controller and a neural controller at least in the sense that their performances are independent of the type of command.
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Control limits consideration in discrete control system design
  • Author(s): G.P. Chen ; O.P. Malik ; G.S. Hope
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 413 –422
  • DOI:  10.1049/ip-d.1993.0054
  • Type: Article
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  • p. 413 –422 (10)
    Consideration of control limits in the design of discrete control system and their impact on system performance is discussed in this paper. The mechanism of how the control limits influence the closed loop system behaviour is investigated using an approach different from that commonly adopted in the literature. Theoretical analysis in this paper reveals the effect of control limits in the form of a short-term behaviour of the controlled system. This phenomenon is investigated by introducing a concept of ‘short-term behaviour index’. With the introduction of ‘dynamic control limits’, an effective discrete control system design method is proposed to handle this problem.
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Robust control design for discrete time linear uncertain systems with delayed control
Decentralised feedback controllers for uncertain interconnected dynamic systems
  • Author(s): H. Trinh  and  M. Aldeen
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 429 –434
  • DOI:  10.1049/ip-d.1993.0056
  • Type: Article
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  • p. 429 –434 (6)
    This paper presents a method for the design of decentralised controllers for interconnected dynamic systems with structured uncertainties. The design problem is formulated as a constrained linear quadratic optimal regulator problem, where the cost function is designed to incorporate the system uncertainties. Conditions are then derived for choosing the state and control weighting matrices that guarantee closed-loop stability in the presence of the uncertainties. Once these matrices are appropriately chosen, a generalised Riccati equation is solved and a robust decentralised controller is obtained. Two numerical examples are given to illustrate the controller design method.
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Roll loop design for bank-to-turn guidance by polynomial methods
  • Author(s): N.E. Parkes ; A.P. Roberts ; H. Wilson
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 435 –441
  • DOI:  10.1049/ip-d.1993.0057
  • Type: Article
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  • p. 435 –441 (7)
    Computer programs, based on the polynomial approach, have been used to design fixed, linear, optimal roll loop controllers using typical plant and disturbance models. Design parameters may be adjusted to produce systems which satisfy a hard limit on aileron angle and which have a range of step responses. The controller complexity may be reduced as part of the design process. The performance of the resulting single-loop system is examined and compared with that of the corresponding double loop design in which roll rate as well as roll angle is fed back. In cases where weathercock oscillation is a problem, it is demonstrated how the system attenuation at the weathercock frequency might be increased. The details of a worked example are given in Appendix 8 to illustrate the design method.
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Hybrid learning algorithm for Gaussian potential function networks
  • Author(s): C.-L. Chen ; W.-C. Chen ; F.-Y. Chang
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 442 –448
  • DOI:  10.1049/ip-d.1993.0058
  • Type: Article
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  • p. 442 –448 (7)
    A new hybrid learning algorithm is proposed for use in the parametric estimation of Gaussian potential function networks (GPFNs). In the new algorithm, the number of network inputs is augmented by using target output values in the learning centres of Gaussian nodes in the network's hidden layer. This augmentation of input leads to a more reasonable distribution of centres in the hidden layer of a GPFN. A critical angle technique is then used to determine those nodes in which the shape factors will need further tuning by optimisation techniques. Two numerical examples are supplied to show the superior performance of this new algorithm as compared to that achieved through a traditional hybrid learning method, or to the optimised-only method of Lee and Kil. The capability of the GPFN as a dynamical model for continually tracking dynamics of non-stationary and time-varying systems is also illustrated.
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Homotopy methods for the solution of general modified algebraic Riccati equations
Model conversions of uncertain linear systems using the Pade and inverse-Pade method
  • Author(s): L.S. Shieh ; J. Gu ; Y.L. Bao
  • Source: IEE Proceedings D (Control Theory and Applications), Volume 140, Issue 6, p. 455 –464
  • DOI:  10.1049/ip-d.1993.0060
  • Type: Article
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  • p. 455 –464 (10)
    The paper presents a mixed method consisting of the Pade approximation and the inverse-Pade approximation method for model conversions of a continuous-time (discrete-time) structured uncertain linear system to an equivalent discrete-time (continuous-time) structured uncertain linear model. This allows the use of well-developed theorems and algorithms in the discrete-time (continuous-time) domain to indirectly solve the continuous-time (discrete-time) domain problems. When the ratio of the uncertainties (ΔA, ΔB) to the nominal system parameters (Ao, Bo) and/or the sampling period (T ≤ 2/(∥Ao ∥ + ∥ΔA∥)) are sufficiently small, the linearised uncertain models can be obtained by neglecting the nonlinear uncertain terms, O(T2 ΔA2) and O(T2ΔAΔB), in the state-space models. The comparison of a high-order Pade approximate model with the bilinear approximate model and the Taylor-series approximate model is also presented. Moreover, this paper also presents a method to estimate tighter bounds of discrete-time (continuous-time) structured uncertainties based on the given continuous-time (discrete-time) structured uncertainties.
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