关键词：光机电；机器人；多目标优化；微分进化
摘 要：This paper presents a method based on a multi-objective self-adaptive differential evolution (MOSaDE) algorithm to improve the parametric reconfiguration feature in the optimal design of a parallel robot.We propose a MOSaDE algorithm,in which both trial vector generation strategies and their associated control parameter values are gradually self-adapted by learning from their previous experiences in generating promising solutions.Consequently,a more suitable generation strategy along with its parameter settings can be determined adaptively to match different phases of the search process.Furthermore,a constraint-handling mechanism is added to bias the search to the feasible region of the search space.The obtained solution will be a set of optimal geometric parameters and optimal PID control gains.The results obtained in a set of experiments performed mechatronic system show the effectiveness of the proposed approach.