Showing papers by "Hassan K. Khalil published in 1986"

Singular perturbation methods in control : analysis and design

Abstract: From the Publisher: Singular perturbations and time-scale techniques were introduced to control engineering in the late 1960s and have since become common tools for the modeling, analysis, and design of control systems. In this SIAM Classics edition of the 1986 book, the original text is reprinted in its entirety (along with a new preface), providing once again the theoretical foundation for representative control applications. This book continues to be essential in many ways. It lays down the foundation of singular perturbation theory for linear and nonlinear systems, it presents the methodology in a pedagogical way that is not available anywhere else, and it illustrates the theory with many solved examples, including various physical examples and applications. So while new developments may go beyond the topics covered in this book, they are still based on the methodology described here, which continues to be their common starting point. Audience Control engineers and graduate students who seek an introduction to singular perturbation methods in control will find this text useful. The book also provides research workers with sketches of problems in the areas of robust, adaptive, stochastic, and nonlinear control. No previous knowledge of singular perturbation techniques is assumed. About the Authors Petar Kokotovic is Director of the Center for Control Engineering and Computation at the University of California, Santa Barbara. Hassan K. Khalil is Professor of Electrical and Computer Engineering at Michigan State University. John O'Reilly is Professor of Electronics and Electrical Engineering at the University of Glasgow, Scotland.

Adaptive stabilization of a class of nonlinear systems using high-gain feedback

Abstract: This paper presents a high-gain feedback stabilizing control algorithm in which the high-gain parameter is adapted on line. The algorithm is developed for a class of nonlinear systems which can be viewed as the nonlinear counterpart of uniform rank multivariable linear systems. The system can be unknown except for a number of vital pieces of information. For single-input single-output linear systems such information is usually required in the traditional adaptive control literature.

Adaptive Stabilization of SISO Systems with Unknown High-Frequency Gains

Abstract: This paper presents an algorithm for adaptively stabilizing a single-input single output system admitting any minimum phase plant of relative degree q. A priori knowledge of the sign of the plant's high frequency gain and an upper bound on the plant order is not needed.

Output feedback stabilization of singularly perturbed systems

Abstract: Output feedback control of linear time-invariant singularly perturbed systems is studied. The set of all compensators that stabilize a singularly perturbed system while preserving its two-time-scale structure is parametrized. The parametrization is used to show that any two-frequency-scale stabilizing compensator can be asymptotically approximated by a compensator designed via a sequential procedure. In this procedure, a fast (high-frequency) compensator is designed first to stabilize the fast model of the system. Then, a strictly proper slow (low-frequency) compensator is designed to stabilize a modified slow model. The parallel connection of the two compensators forms a two-frequency-scale stabilizing compensator for the singularly perturbed system.