Global Convergence of a Decentralized Adaptive Fuzzy Control for the Motion of Robot Manipulators: Application to the Mitsubishi PA10-7CE as a Case of Study

In general terms, robot control consists in making a robot execute a commanded task. One of the most important cases is the trajectory tracking or motion control. In this paper, a control algorithm that uses adaptive fuzzy systems to approximate local portions of the robot manipulator dynamics is proposed in order to solve the trajectory tracking problem. This scheme is characterized by not requiring any knowledge of the dynamic model and, in contrast to some fuzzy adaptive controllers previously developed, the one proposed here is in a decentralized configuration, wherein each joint is considered as a subsystem and is independently controlled only through its local variables. Furthermore, a study that guarantees the stability and the boundedness of the solutions of the closed-loop system via Lyapunov theory is presented, including a functional analysis which proves for the first time that a decentralized adaptive fuzzy controller satisfies the motion control objective. The theoretical results exposed here are verified via experimentation by applying the designed algorithm to the Mitsubishi PA10-7CE robot arm and the outcomes are reported.