1st Edition

Neural Network Control of Nonlinear Discrete-Time Systems

By Jagannathan Sarangapani Copyright 2006
    622 Pages 171 B/W Illustrations
    by CRC Press

    Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems.

    Borrowing from Biology
    Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts.

    Progressive Development
    After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware.

    Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.

    BACKGROUND ON NEURAL NETWORKS
    NN Topologies and Recall
    Properties of NN
    NN Weight Selection and Training
    NN Learning and Control Architectures
    References
    Problems
    BACKGROUND AND DISCRETE-TIME ADAPTIVE CONTROL
    Dynamical Systems
    Mathematical Background
    Properties of Dynamical Systems
    Nonlinear Stability Analysis and Controls Design
    Robust Implicit STR
    References
    Problems
    Appendix 2.A
    NEURAL NETWORK CONTROL OF NONLINEAR SYSTEMS AND FEEDBACK LINEARIZATION
    NN Control with Discrete-Time Tuning
    Feedback Linearization
    NN Feedback Linearization
    Multilayer NN for Feedback Linearization
    Passivity Properties of the NN
    Conclusions
    References
    Problems
    NEURAL NETWORK CONTROL OF UNCERTAIN NONLINEAR DISCRETE-TIME SYSTEMS WITH ACTUATOR NONLINEARITIES
    Background on Actuator Nonlinearities
    Reinforcement NN Learning Control with Saturation
    Uncertain Nonlinear System with Unknown Deadzone and Saturation Nonlinearities
    Adaptive NN Control of Nonlinear System with Unknown Backlash
    Conclusions
    References
    Problems
    Appendix 4.A
    Appendix 4.B
    Appendix 4.C
    Appendix 4.D
    OUTPUT FEEDBACK CONTROL OF STRICT FEEDBACK NONLINEAR MIMO DISCRETE-TIME SYSTEMS
    Class of Nonlinear Discrete-Time Systems
    Output Feedback Controller Design
    Weight Updates for Guaranteed Performance
    Conclusions
    References
    Problems
    Appendix 5.A
    Appendix 5.B
    NEURAL NETWORK CONTROL OF NONSTRICT FEEDBACK NONLINEAR SYSTEMS
    Introduction
    Adaptive NN Control Design Using State Measurements
    Output Feedback NN Controller Design
    Conclusions
    References
    Problems
    Appendix 6.A
    Appendix 6.B
    SYSTEM IDENTIFICATION USING DISCRETE-TIME NEURAL NETWORKS
    Identification of Nonlinear Dynamical Systems
    Identifier Dynamics for MIMO Systems
    NN Identifier Design
    Passivity Properties of the NN
    Conclusions
    References
    Problems
    DISCRETE-TIME MODEL REFERENCE ADAPTIVE CONTROL
    Dynamics of an mnth-Order Multi-Input and Multi-Output System
    NN Controller Design
    Projection Algorithm
    Conclusions
    References
    Problems
    NEURAL NETWORK CONTROL IN DISCRETE-TIME USING HAMILTON-JACOBI-BELLMAN FORMULATION
    Optimal Control and Generalized HJB Equation in Discrete-Time
    NN Least-Squares Approach
    Numerical Examples
    Conclusions
    References
    Problems
    NEURAL NETWORK OUTPUT FEEDBACK CONTROLLER DESIGN AND EMBEDDED HARDWARE IMPLEMENTATION
    Embedded Hardware-PC Real-Time Digital Control System
    SI Engine Test Bed
    Lean Engine Controller Design and Implementation
    EGR Engine Controller Design and Implementation
    Conclusions
    References
    Problems
    Appendix 10.A
    Appendix 10.B
    INDEX

    Biography

    Sarangapani, Jagannathan