PID Gain Tuning Using Genetic Algorithms and Fuzzy Logic for Robot Manipulator Control

This paper addresses an application that involves the control of robot manipulator joint. It presents a PID tuning method that uses a Genetic Algorithm (GA) as a main gain estimator and a fuzzy logic as a ranking basement for GA. The suggested approach is then used to tune the PID gains for different response specifications. Experimental results demonstrate that better performance can be achieved with this fuzzy based GA-PID tuning relative to 1) Ziegler-Nichols tuning and 2) trial and error tuning. This paper tries to explore the potential of using soft computing methodologies in control of plant (robot manipulator) with internal behavior of structure-unknown non-linear time variant dynamic systems. Industrial robot manipulator was used for the case study in this work. The manipulator is simulated with professional simulation software (consist of Solid work, Visual Nastran 4D and Matlab/Simulink).