Angle Error-Tracking Iterative Learning Control for Pneumatic Artificial Muscle System

Qiyao Yang,Wei Wang,Jianping Cai,Qiuzhen Yan,Yuntao Zhang

doi:10.1109/access.2021.3133864

Abstract

In this paper, a novel angle error-track adaptive iterative learning control scheme is proposed to solve the angle tracking problem for a pneumatic artificial muscle-actuated mechanism with nonzero initial errors. Lyapunov synthesis is used to design the adaptive learning controller and analyze the stability of closed-loop PAM system. Firstly, the system modeling for the PAM-actuated mechanism is introduced as a preparation of controller design. Then, the reference error trajectory is constructed to deal with the initial position problem of iterative learning control. The parametric uncertainties in the controlled system are estimated by using difference learning method. Robust control strategy is used to deal with nonparametric uncertainties and disturbances. By making the system error follow the desired error trajectory over the whole time interval as the iteration number increases, we derive the accurate tracking from the system state to the reference trajectory during the predetermined part time interval. Simulation results show the effectiveness of the propose angle error-tracking adaptive ILC scheme.

Highlights

Pneumatic artificial muscle (PAM) is a novel nonlinear biomimetic actuator, whose structure and functionality differs significantly from traditional actuators, such as motors, hydraulic actuators and gas cylinders
For applying ILC technique into industrial processes, researchers have to investigate how to remove the assumption of zero initial error in iterative learning controller design
Motivated by the above discussion, this work focuses on the adaptive ILC algorithm design for PAM systems with nonzero initial errors

Summary

INTRODUCTION

Pneumatic artificial muscle (PAM) is a novel nonlinear biomimetic actuator, whose structure and functionality differs significantly from traditional actuators, such as motors, hydraulic actuators and gas cylinders. Through the continuous efforts over the last three decades, many significant ILC theoretical results have been obtained, which promotes the practical applications of ILC technique [39]- [44] For those PAM-actuated mechanisms performing repeated tasks in rehabilitation, assembly lines and other situations, ILC is a proper technique to implement high-precision control. For applying ILC technique into industrial processes, researchers have to investigate how to remove the assumption of zero initial error in iterative learning controller design. This problem is called the initial position problem of ILC. Motivated by the above discussion, this work focuses on the adaptive ILC algorithm design for PAM systems with nonzero initial errors.

PROBLEM FORMULATION

CONSTRUCTION OF DESIRED ERROR TRAJECTORY

CONVERGENCE ANALYSIS

NUMERICAL SIMULATION

CONCLUSION