A Novel Neuro PID Controller of Remotely Operated Robotic Manipulators

Abstract

Motivated by the demand of intelligent control that applicable to real industrial systems, this brief develops an innovative neuro controller for remotely operated robotic manipulators. First, the leader-following robotic devices and their communication are introduced. The remotely operated robot can either be controlled by pre-designed controller or human-computer interaction. Then, a neuro network algorithm is utilized to update PID control gains adaptively. To minimize training time, adaptive moment estimation algorithm is integrated to the neuro PID controller to form a novel control strategy which can be implemented in closed loop. As a result, intelligent algorithms and control methodology can be combined to solve industrial problem. Furthermore, the proposed intelligent controllers are implemented to two cases of remotely operated robot: 1. pre-designed motion driven for comparison; 2. Human-computer interaction. Real experimental results can successfully validate the effectiveness of the presented techniques.