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Gain tuning is very important in order to obtain good performances for a given controller. Contour tracking performance is mainly determined by the selected control gains of a position domain PID controller. In this paper, three popular evolutionary algorithms are utilized to optimize the gains of a position domain PID controller for performance improvement of contour tracking of robotic manipulators. Differential Evolution (DE), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are used to determine the optimal gains of the position domain PID controller, and three distinct fitness functions are also used to quantify the contour tracking performance of each solution set. Simulation results show that DE features the highest performance indexes for both linear and nonlinear contour tracking, while PSO is quite efficient for linear contour tracking. Both algorithms performed consistently better than GA that featured premature convergence in all cases.

In this paper, a new position domain synchronization control (PDSC) law is proposed for contour control of multi-DOF nonlinear robotic manipulators with the main goal of improving contour tracking performance. The robotic manipulator is treated as a master-slave motion system, where the position of the master motion is used as an independent reference via equidistant sampling, and the slave motions are described as functions of the master motion. To build this relationship, the dynamics of the original system is transformed from time domain to position domain. The new control introduces synchronization and coupled errors in the control law to further coordinate the master and slave motions. Stability analysis is performed based on the Lyapunov method for the proposed PDSC, and simulations are conducted to verify the effectiveness of the developed control system.