Disturbance Observer for Advanced Motion Control with MATLAB / Simulink

A fulsome and robust presentation of disturbance observers complete with MATLAB sample programs and simulation results

In Disturbance Observer for Advanced Motion Control with MATLAB/Simulink, distinguished electronics engineer Dr. Akira Shimada delivers a comprehensive exploration of the suppression of actual and unknown disturbances. In the book, you’ll find a systematic discussion of the basic theory and design methods of disturbance observers accompanied by instructive MATLAB and Simulink simulation examples.

Included appendices cover the mathematical background of classical, modern, and digital control and ground the reader’s understanding of the more advanced sections. The included material is ideal for students enrolled in courses in advanced motion control, mechatronics system control, electrical drives, motion control, robotics, and aeronautics.

In addition to topics like model predictive control, vibration systems, acceleration control, adaptive observers, and multi-rate sampling, readers will find:

• A thorough introduction to the various types of disturbance observers and the fundamentals of disturbance observers, including disturbance estimation and disturbance rejection
• Comprehensive explorations of stabilized control and coprime factorization, including the derivation of stabilizing controllers
• Practical discussions of disturbance observers in state space, including identity input disturbance observers and identity reaction force observers
• Fulsome treatments of the mathematical foundations of control theory, methods??for measuring and estimating velocities, and the disturbance estimation Kalman filter

Perfect for undergraduate and graduate students with existing knowledge of the fundamentals of control engineering who wish to learn how to design disturbance observers, Disturbance Observer for Advanced Motion Control with MATLAB/Simulink will also benefit professional engineers and researchers studying alternative control theories.