Discrete-Time Inverse Optimal Control for Nonlinear Systems: 1st Edition (Paperback) book cover

Discrete-Time Inverse Optimal Control for Nonlinear Systems

1st Edition

By Edgar N. Sanchez, Fernando Ornelas-Tellez

CRC Press

268 pages | 10 Color Illus. | 70 B/W Illus.

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Description

Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller.

Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems

The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). The synthesized discrete-time optimal controller can be directly implemented in real-time systems. The book also proposes the use of recurrent neural networks to model discrete-time nonlinear systems. Combined with the inverse optimal control approach, such models constitute a powerful tool to deal with uncertainties such as unmodeled dynamics and disturbances.

Learn from Simulations and an In-Depth Case Study

The authors include a variety of simulations to illustrate the effectiveness of the synthesized controllers for stabilization and trajectory tracking of discrete-time nonlinear systems. An in-depth case study applies the control schemes to glycemic control in patients with type 1 diabetes mellitus, to calculate the adequate insulin delivery rate required to prevent hyperglycemia and hypoglycemia levels.

The discrete-time optimal and robust control techniques proposed can be used in a range of industrial applications, from aerospace and energy to biomedical and electromechanical systems. Highlighting optimal and efficient control algorithms, this is a valuable resource for researchers, engineers, and students working in nonlinear system control.

Table of Contents

Introduction

Inverse Optimal Control via Passivity

Inverse Optimal Control via CLF

Neural Inverse Optimal Control

Motivation

Mathematical Preliminaries

Optimal Control

Lyapunov Stability

Robust Stability Analysis

Passivity

Neural Identification

Inverse Optimal Control: A Passivity Approach

Inverse Optimal Control via Passivity

Trajectory Tracking

Passivity-based Inverse Optimal Control for a Class of Nonlinear Positive Systems

Conclusions

Inverse Optimal Control: A CLF Approach, Part I

Inverse Optimal Control via CLF

Robust Inverse Optimal Control

Trajectory Tracking Inverse Optimal Control

CLF-based Inverse Optimal Control for a Class of Nonlinear Positive Systems

Conclusions

Inverse Optimal Control: A CLF Approach, Part II

Speed-Gradient Algorithm for the Inverse Optimal Control

Speed-Gradient Algorithm for Trajectory Tracking

Trajectory Tracking for Systems in Block-Control Form

Conclusions

Neural Inverse Optimal Control

Neural Inverse Optimal Control Scheme

Block-Control Form: A Nonlinear Systems Particular Class

Conclusions

Glycemic Control of Type 1 Diabetes Mellitus Patients

Introduction

Passivity Approach

CLF Approach

Conclusions

Conclusions

References

About the Authors

Edgar N. Sanchez is a researcher at CINVESTAV-IPN, Guadalajara Campus, Mexico. He was granted a U.S. National Research Council Award as a research associate at NASA Langley Research Center (January 1985-March 1987). He is also a member of the Mexican National Research System (promoted to the highest rank, III, in 2005), the Mexican Academy of Science, and the Mexican Academy of Engineering. He has published more than 100 technical papers in international journals and conferences, and has served as reviewer for various international journals and conferences. His research interest centers on neural networks and fuzzy logic as applied to automatic control systems.

Fernando Ornelas-Tellez is currently a professor of electrical engineering at Michoacan University of Saint Nicholas of Hidalgo, Mexico. His research interests center on neural control, direct and inverse optimal control, passivity and their applications to biomedical systems, electrical machines, power electronics, and robotics.

About the Series

System of Systems Engineering

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Subject Categories

BISAC Subject Codes/Headings:
TEC007000
TECHNOLOGY & ENGINEERING / Electrical
TEC008000
TECHNOLOGY & ENGINEERING / Electronics / General