Lyapunov-Based Control of Robotic Systems describes nonlinear control design solutions for problems that arise from robots required to interact with and manipulate their environments. Since most practical scenarios require the design of nonlinear controllers to work around uncertainty and measurement-related issues, the authors use Lyapunov’s direct method as an effective tool to design and analyze controllers for robotic systems.
After describing the evolution of real-time control design systems and the associated operating environments and hardware platforms, the book presents a host of standard control design tools for robotic systems using a common Lyapunov-based framework. It then discusses several problems in visual servoing control, including the design of homography-based visual servo control methods and the classic structure from motion problem. The book also deals with the issues of path planning and control for manipulator arms and wheeled mobile robots. With a focus on the emerging research area of human machine interaction, the final chapter illustrates the design of control schemes based on passivity such that the machine is a net energy sink.
Including much of the authors’ own research work in controls and robotics, this book facilitates an understanding of the application of Lyapunov-based control design techniques to up-and-coming problems in robotics.
Table of Contents
History of Robotics
Lyapunov-Based Control Philosophy
The Real-Time Computer Revolution
Modeling and Control Objective
Computed Torque Control Approaches
Adaptive Control Design
Task-Space Control and Redundancy
Monocular Image-Based Geometry
Visual Servo Tracking
Mobile Robot Regulation and Tracking
Structure from Motion
Path Planning and Control
Velocity Field and Navigation Function Control for Manipulators
Velocity Field and Navigation Function Control for WMRs
Optimal Navigation and Obstacle Avoidance
Human Machine Interaction
Appendix A: Mathematical Background
Appendix B: Supplementary Lemmas and Expressions
References appear at the end of each chapter.
Aman Behal is an assistant professor in the School of Electrical Engineering and Computer Science and the NanoScience Technology Center at the University of Central Florida.
Warren Dixon is an associate professor and director of the Nonlinear Controls and Robotics group in the Department of Mechanical and Aerospace Engineering at the University of Florida.
Darren M. Dawson is McQueen Quattlebaum Professor and chair of the Holcombe Department of Electrical and Computer Engineering at Clemson University.
Bin Xian is a professor in the School of Electrical Engineering and Automation at Tianjin University.