IEE Proceedings D (Control Theory and Applications)

IEE Proceedings D (Control Theory and Applications)

Online ISSN 2053-793X
Print ISSN 0143-7054

Published from 1980-1993, IEE Proceedings D contained significant and original contributions on control theory and its applications. It was devoted to control systems in the broadest sense, covering new theoretical results and the applications of new and established control methods.

This journal was previously known as Proceedings of the Institution of Electrical Engineers 1963-1979. ISSN 0020-3270. more..

This publication is continued by IEE Proceedings - Control Theory and Applications 1994-2006. ISSN 1350-2379. more..

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Generalised command matching for a robot gripping an inertial load
- Author(s): P.N. Paraskevopoulos ; F.N. Koumboulis ; K.G. Tzierakis
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- p. 373 –379 (7)
  The problem of controlling a robot with end effector rigidly gripping an inertial load is studied using the generalised command-matching technique via proportional state feedback. In particular, the necessary and sufficient conditions for the problem to have a solution are established and the general analytical expressions of the controller matrices are derived. Structural properties of the resulting closed-loop system are also investigated.
State space based adaptive control with pole restriction
- Author(s): M.S. Ahmed
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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.
Direct adaptive output tracking control using multilayered neural networks
- Author(s): L. Jin ; P.N. Nikiforuk ; M.M. Gupta
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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.
Self-tuning control using the right-matrix-fraction innovation description
- Author(s): M.S. Ahmed
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- p. 399 –404 (6)
  An algorithm for self-tuning control of discrete-time linear plant is proposed. The algorithm uses a stochastic right-matrix-fraction innovation description as the system representation, a recursive-prediction-error algorithm for online estimation of the system parameters and the costates, and pole placement plus moving-average control via costate and innovation feedback.
Intelligent supervision of servo control
- Author(s): M.H. Perng and H.H. Chang
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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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IEE Proceedings D (Control Theory and Applications)

Volumes & issues:

Volume 140 (1993)

Volume 139 (1992)

Volume 138 (1991)

Volume 137 (1990)

Volume 136 (1989)

Volume 135 (1988)

Volume 134 (1987)

Volume 133 (1986)

Volume 132 (1985)

Volume 131 (1984)

Volume 130 (1983)

Volume 129 (1982)

Volume 128 (1981)

Volume 127 (1980)

Latest content

Generalised command matching for a robot gripping an inertial load

State space based adaptive control with pole restriction

Direct adaptive output tracking control using multilayered neural networks

Self-tuning control using the right-matrix-fraction innovation description

Intelligent supervision of servo control

Most viewed content for this Journal

Most cited content for this Journal