PID Control with Intelligent Compensation for Exoskeleton Robots

  • ID: 4335162
  • Book
  • 234 Pages
  • Elsevier Science and Technology
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PID Control with Intelligent Compensation for Exoskeleton Robots explains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability.

Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering.

  • Discusses novel PD and PID controllers for biomedical and industrial robotic applications, demonstrating how PD and PID with intelligent compensation is more effective than other model-based compensations
  • Presents a stability analysis of the book for industrial linear PID
  • Includes practical applications of robotic PD/PID control, such as serial sliding mode, explicit conditions for linear PID and high gain observers for neural PD control
  • Includes applied exoskeleton applications and MATLAB code for simulations and applications

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1. Preliminaries 2. Stable PID Control and Systematic Tuning of PID Gains 3. PID Control in Task Space 4. PD Control with Neural Compensation 5. PID Control with Neural Compensation 6. PD Control with Fuzzy Compensation 7. PD Control with Sliding Mode Compensation 8. PID Admittance Control in Task Space 9. PID Admittance Control in Joint Space 10. Robot Trajectory Generation in Joint Space 11. Appendix
Design of Upper Limb Exoskeletons

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Yu, Wen
Wen Yu received the B.S. degree from Tsinghua University, Beijing, China in 1990 and the M.S. and Ph.D. degrees, both in Electrical Engineering, from Northeastern University, Shenyang, China, in 1992 and 1995, respectively. Since 1996, he has been with the
National Polytechnic Institute (CINVESTAV-IPN), Mexico City, Mexico, where he is currently a professor and department chair of the Automatic Control Department. From 2002 to 2003, he held research positions with the Mexican Institute of Petroleum. He was a Senior Visiting Research Fellow with Queen's University Belfast, Belfast, U.K., from 2006 to 2007, and a Visiting Associate Professor with the University of California, Santa Cruz, from 2009 to 2010. He gas published more than 100 research papers in reputed journals. His Google Scholar h-index is 33, the citation number is 4100. He serves as associate editors of IEEE Transactions on Cybernetics, Neurocomputing, and Journal of Intelligent and Fuzzy Systems. He is a member of the Mexican Academy of Sciences.
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