Jixie chuandong (Apr 2019)
Artificial Bee Colony and Newton Algorithm for Forward Position Solution of Parallel Mechanism
Abstract
By an organic combination of the intelligent optimization algorithm and the numerical iteration method， a general algorithm called hybrid artificial bee colony and Newton iteration （HABC-Newton） algorithm for solving the forward positions of parallel mechanism is constructed. The differential evolution （DE） algorithm is incorporated into the artificial bee colony （ABC） algorithm to form a hybrid ABC （HABC） algorithm which can converge quickly to the near optimal solution of the problem. Then the optimal solution is used as initial value and Newton-Шамарский iteration method is employed to find high precision solutions. Taking 4-SPS-CU parallel mechanism kinematics analysis as an example， the forward kinematics analysis method of parallel mechanism based on HABC-Newton algorithm is stated. In order to verify the effectiveness and universality of the algorithm， two numerical examples of forward kinematics such as 4-SPS-CU and 3-RRR coupled parallel mechanisms are given. The results show that the HABC-Newton algorithm can obtain all the high accurate solutions of the parallel mechanism with less computational cost. Furthermore， comparative tests to solve these examples are carried out with HABC-Newton， ABC， DE and particle swarm optimization algorithms， and the numerical experiments indicate that HABC-Newton algorithm has better performance than compared algorithms in terms of the accuracy， robustness and computational efficiency.
