Optimal fuzzy inverse dynamics control of a parallelogram mechanism based on a new multi-objective PSO. Issue 1 (1st January 2018) - Farokhi, A.; Mahmoodabadi, M.J.
Abstract: This work presents a multi-objective optimization method based on high exploration particle swarm optimization, called MOHEPSO, for optimization problems with multiple objectives. In order to convert the single-objective (HEPSO) algorithm to the multi-objective one, its fundamentals should be changed. The leaders' selection in the proposed algorithm is based on the neighborhood radius concept for the global best position and the Sigma method for the personal best position. Also, a fuzzy elimination technique is used for pruning the archive. The numerical results of the MOHEPSO algorithm on mathematical test functions are compared with those of other multi-objective optimization algorithms for the performance evaluation of the algorithm. Finally, the proposed algorithm is implemented to find the optimum values of controller coefficients for a parallelogram five-bar linkage mechanism. The introduced control strategy is designed based on the inverse dynamics concepts, improved by fuzzy systems and optimized by regarding two objective functions. The simulation results are presented to demonstrate the efficiency and accuracy of this approach.