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An optimized fuzzy logic controller for a parallel mechanism rehabilitation robot

机译:并联机构康复机器人的优化模糊逻辑控制器

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This paper focuses on the trajectory tracking control of the two-degree-of-freedom parallel manipulator. In order to have a robust tracking a fuzzy logic controller of which the boundary scales of the membership functions are optimized is developed. The performance of the developed optimized fuzzy logic controller is compared to the optimized proportional-integral-derivative controller. Particle swarm optimization algorithm is used with a fitness function, integral of time weighted absolute error (ITAE) performance index, during the optimization process. The performances of both controllers are measured using the ITAE performance index. In addition, other error-based objective functions called integral of squared error (ISE), integral of absolute error (IAE) and integral of time weighted squared error (ITSE) are calculated for a better comparison of the controllers. The results of the simulations show that the developed optimized fuzzy logic controller has better tracking performance compared to optimized proportional-integral-derivative controller.
机译:本文重点研究了两自由度并联机械手的轨迹跟踪控制。为了具有鲁棒的跟踪,开发了模糊逻辑控制器,该模糊逻辑控制器的隶属函数的边界尺度得到了优化。将开发的优化模糊逻辑控制器的性能与优化的比例积分微分控制器进行比较。在优化过程中,将粒子群优化算法与适应度函数(时间加权绝对误差(ITAE)性能指标的整数)配合使用。这两个控制器的性能均使用ITAE性能指标来衡量。另外,还计算了其他基于误差的目标函数,称为平方误差积分(ISE),绝对误差积分(IAE)和时间加权平方误差积分(ITSE),以更好地比较控制器。仿真结果表明,与优化的比例-积分-微分控制器相比,开发的优化的模糊逻辑控制器具有更好的跟踪性能。

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