改进多目标PSO算法优化机器人轨迹跟踪模糊PID控制器

Multi-objective PSO-based fuzzy PID controller for robot trajectory tracking

为进一步提高模糊PID控制器应用于关节机器人轨迹跟踪控制的效果,本文提出了一种改进的多目标粒子群(PSO)算法优化机器人轨迹跟踪模糊PID控制器的方法。首先,设计了一种关节机器人轨迹跟踪模糊PID控制器;其次,考虑控制器输出力矩和轨迹跟踪控制偏差2个优化目标,设计了改进多目标PSO算法实现模糊PID控制器隶属函数与模糊规则的优化调整;最后,分别采用多目标PSO算法和改进多目标PSO算法优化轨迹跟踪模糊PID控制器获得了2个优化目标的向量集合,并对比分析了优化结果。实验结果表明,所设计的改进多目标PSO算法具有更优的非支配解集,验证了该算法优化机器人轨迹跟踪模糊PID控制器的有效性和优越性。

In order to improve the control effect of fuzzy PID controller applied to the trajectory tracking control of joint robots,a novel modified multi-objective Particle Swarm Optimization(PSO)is used to optimize robot trajectory tracking fuzzy PID controller.Firstly,a fuzzy PID controller for robot trajectory tracking is designed.And further,considering the optimization goals of controller output torque and trajectory tracking control error,a modified multiobjective PSO algorithm is designed to optimize membership functions and fuzzy rules of the fuzzy PID controller.Finally,multi-objective PSO and modified multi-objective PSO are used to optimize the trajectory tracking fuzzy PID control to obtain the set of optimization goals vector,and the optimization results are compared and analyzed.The experimental results show that the designed modified multi-objective PSO has a better non-dominated solution set,which verifies effectiveness and superiority of the designed algorithm in robot trajectory tracking fuzzy PID control optimization.