|Statement||W.C. Lai ; supervised by P.A. Cook.|
|Contributions||Cook, P.A., Electrical Engineering and Electronics.|
Adaptive Stabilization of Discrete-Time Nonminimum Phase Systems Abstract: In this paper, we present a direct multirate adaptive control algorithm that ensures global stabilization of a class of (potentially unstable and invertible) linear time-invariant discrete-time plants of known order and relative degree by: 2. SUMMARY This book covers crucial lacunae of the linear discrete-time time-invariant dynamical systems and introduces the reader to their treatment, while functioning under real, natural conditions. Abstract: This paper demonstrates tracking control of a class of unknown nonlinear dynamical systems using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLCs are implemented on digital computers. A repeatable design algorithm and a stability proof are presented for an adaptive fuzzy logic controller that uses basis vectors based. Stability results for discrete-time linear systems subject to random jumps in the parameters are obtained. First, necessary and sufficient conditions for mean square stability (MSS), including the case in which the system is driven by an independent wide-sense stationary random sequence, are derived.
This paper studies the global output tracking problem for a class of unknown time-varying nonlinear systems in strict-feedback form. By utilizing the barrier functions, a universal adaptive state-feedback control strategy is proposed that achieves asymptotic tracking performance. Most of the existing results on adaptive control of discrete-time systems are concerned with the case where the unknown parameters enter into the system in a linear way. For systems with nonlinearly parameterized unknown parameters, one problem in constructing the controller lies in the fact that the traditional least squares and gradient estimation based adaptive controller will have. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.
This paper presents a novel discrete-time sliding mode control (DSMC) for a general class of discrete-time chaotic systems with input nonlinearity and uncertainties. Unlike the co. In this paper, adaptive neural network (NN) control is investigated for a class of single-input single-output (SISO) discrete-time unknown non-linear systems with general relative degree in the. The core of this textbook is a systematic and self-contained treatment of the nonlinear stabilization and output regulation problems. Its coverage embraces both fundamental concepts and advanced research outcomes and includes many numerical and practical examples. Several classes of important uncertain nonlinear systems are discussed. In this paper, adaptive control is studied for a class of nonlinear discrete-time systems in strict-feedback form with unknown control directions. The system is transformed to an n-step ahead.