One solution to enhance the accuracy in the trajectory-tracking of a single-joint robot arm under PID control is to implement a fuzzy PID strategy based on fuzzy logic. Such a controller may describe the nonlinear behavior of the plant without relying on an accurate mathematical representation of the controlled object, but it also maintains the standard PID structure. To further meet the optimization demands of the trajectory tracking, the Dynamic Population Dead-Zone-Initiated Adaptive Particle Swarm Optimization algorithm (DP-DZIA-PSO) is applied to adjust the fuzzy PID parameters. On importing a six-degree-of-freedom robotic-arm dynamic model developed in SolidWorks into ADAMS, simulation and motion analysis are performed and the target angular velocity is used to compute the torque required by every joint and thus formulating a foundation of selecting the motor. Then, PSO, DZIA-PSO, and DP-DZIA-PSO are used to minimize the robotic-arm PID control system, and the comparative results of the three methods are obtained. The findings indicate that the enhanced particle-swarm method proposed herein provides a better Pareto front over the other two approaches. Because the controllers associated with various optimization solutions possess different control properties, appropriate solutions may be selected based on particular practical needs.
