Functional Adaptive Control

This book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces. The underlying design philosophy is based on effecting closed-loop control in the presence of plant or environmental uncertainty and complexity by utilizing various types of neural network architectures, ranging from multilayer perceptron to radical basis function and modular network models. The uncertainty and complexity are typified by unknown nonlinear functionals, and temporal or spatial multi-modality. Deterministic and stochastic conditions, as well as continuous and discrete time dynamics are taken into consideration. The presented designs are firmly rooted in the techniques of adaptive control, reconfigurable control, multiple model control, stochastic adaptive control, lyapunov stability theory and neural networks. The techniques are shown to enhance the performance of the control system in the presence of the higher levels of complexity and uncertainty associated with modern plants, which demand superior intelligence and autonomy from the controller. The presented designs are supported both by theory and by numerous results from simulation experiments. The book also includes extensive reviews on general aspects concerning the fields of intelligent, nonlinear and stochastic control.

Contents

• Introduction

Deterministic Systems

• Adaptive Control of Nonlinear Systems
• Dynamic Structure Networks for Stable Adaptive Control
• Composite Adaptive Control of Continuous-time Systems
• Composite Adaptive Control of Continuous-time Systems
• Functional Adaptive Control of Discrete-time Systems

Stochastic Systems

• Stochastic Control
• Dual Adaptive Control of Nonlinear Systems
• Multiple Model Approaches
• Multiple Model Dual Adaptive Control of Jump Nonlinear Systems
• Multiple Model Dual Adaptive Control of Spatial Multi-modal Systems

Epilogue

• Conclusions