PID Controller Optimization for a Three-Link Robot Manipulator Using RGA

This paper presents a novel approach for optimizing Proportional-Integral-Derivative (PID) controllers applied to three-link robot manipulators (RM) using a Real-coded Genetic Algorithm (RGA). The complexity of controlling multilink robotic systems requires advanced optimization techniques to achieve precise and stable performance. Traditional methods of tuning PID controllers often fall short due to the exceedingly nonlinear and correlated dynamics of robotic manipulators. In this study, a Real-coded Genetic Algorithm is utilized to determine the optimal PID controller parameters, enhancing the system's response time, stability, and overall performance. Simulations are conducted to confirm the effectiveness of the proposed optimization method. The results demonstrate substantial enhancements in the manipulators' trajectory tracking and disturbance refutation abilities contrasted to conventional PID tuning methods. This research highlights the potential of genetic algorithms in advancing control strategies for complex robotic systems, offering valuable insights for future developments in robotic control applications.