Design of a Parallel Manipulator Based on Multi-Objective Self-Adaptive Differential Evolution Algorithm

Abstract

In order to improve highly non-isotropic input-output relations in the optimal design of a parallel robot, this paper presents a method based on a multi-objective self-adaptive differential evolution (MOSaDE) algorithm.The approach considers a solution-diversity mechanism coupled with a memory of those sub-optimal solutions found during the process. In theMOSaDE algorithm, both trial vector generation strategies and their associated control parameter values were gradually self-adapted by learning from their previous experiences in generating promising solutions. Consequently, a more suitable generation strategy along with its parameter settings could be determined adaptively to match different phases of the search processevolution.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 empirical analysis of thenumerical results shows the efficiency of the proposed algorithm.

Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm

“…Thus it is desired that the maximum actuator force be also minimized along with the norm of actuator forces. The maximum actuator force in an individual link is given by (26) …”

“…However these research efforts have been limited to a few specific performance criteria to achieve specific design goals. Recently some research work has been done in the field of parallel robot design optimization [24]- [26], however our work differs from the work presented in a manner that we work with robot which has cable based redundant actuation. Contrary to the earlier endeavors, present research work aims to conduct a systematic design analysis of the parallel ankle robot.…”