Development of a qualified PSO fuzzy controller for redundant wheeled robots

Hsu-Chih Huang, Chih-Hao Chiang
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Abstract

This paper presents an optimal fuzzy controller design method using Taguchi theory based particle swarm optimization (TPSO) to four-wheeled redundant mobile robots, called TPSO. In comparison with conventional fuzzy controllers, this approach takes the advantages of Taguchi method, fuzzy control and PSO, thereby obtaining better population diversity, avoiding premature convergence and achieving self-adaptive redundant control. This hybrid computing is then applied to develop an optimal fuzzy controller of redundant autonomous wheeled robots. The optimal parameters of the dynamic controller are self-adaptive via the proposed TPSO to resolve trajectory tracking problem. Simulation results are given to exhibit the merits of the proposed TPSO for redundant wheeled robots.
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冗余轮式机器人合格PSO模糊控制器的研制
提出了一种基于田口理论的粒子群优化(TPSO)的四轮冗余移动机器人模糊控制器优化设计方法。与传统模糊控制器相比,该方法结合了田口法、模糊控制和粒子群算法的优点,获得了更好的种群多样性,避免了过早收敛,实现了自适应冗余控制。然后将这种混合计算应用于冗余自主轮式机器人的最优模糊控制器的开发。利用该算法自适应动态控制器的最优参数,解决了轨迹跟踪问题。仿真结果表明了该算法在冗余轮式机器人控制中的优越性。
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