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针对标准引力搜索算法存在早熟收敛、易陷入局部最优、精度差等问题,提出了一种改进的引力搜索算法。该算法加入三种策略进行改进:采用Tent混沌映射产生初始种群,增加种群多样性;引入线性递减引力常数,提高算法寻优效率;针对进化过程中同一代个体间存在差异的现象,通过引入平均适应度值对种群进行分类,并引入距离因子对不同个体采用不同的惯性权重变化策略,提高算法局部搜索能力。以Delta并联机械手为对象,在满足运动学约束的基础上,将该算法用于4-3-4多项式时间最优轨迹规划中,并与其他算法作比较,仿真结果表明所提算法能有效提高解的精度和收敛速度。
In view of the problems of premature convergence, easy falling into local optimum and poor precision, aiming at the problem of standard gravitation search algorithm, an improved gravitation search algorithm is proposed. The algorithm is improved by adding three strategies: the initial population is generated by Tent chaotic mapping, and the population diversity is increased; linear decreasing gravity constant is introduced to improve the optimization efficiency of the algorithm; in view of the phenomenon that there is a difference between individuals of the same generation in the evolutionary process, Fitness value of the population classification, and the introduction of distance factors for different individuals using different inertia weight change strategy to improve the local search ability of the algorithm. Based on the kinematic constraints, this algorithm is applied to the optimal path planning of 4-3-4 polynomial with Delta parallel manipulator and compared with other algorithms. The simulation results show that the proposed algorithm can effectively improve Solution accuracy and convergence speed.