Neural-based fuzzy logic control for robot manipulators

Abstract

One of the simplest tracking controllers for industrial robot manipulators is the PID control. However, in practice, because it is considerably difficult to determine the PID parameters suitably, many studies have been reported on the tuning method of the PID parameters. The objective of the paper is to design a self-tuning PID controller for achieving time-varying tracking control of a robot manipulator. We present a fuzzy neural network (FNN), which is used to automate the parameters tuning of the PID controller. Some experimental test results are also included to demonstrate the improvement in the tracking performance when the proposed method is used.