Fuzzy Control for Pneumatic Muscle Tracking Via Evolutionary Tuning
Fuzzy Control for Pneumatic Muscle Tracking Via Evolutionary Tuning
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DOI：
10.1080/10798587.2000.10642856
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
X. Chang;J. Lilly
中科院分区：
文献类型：
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作者：
X. Chang;J. Lilly
摘要针对实际气动人工肌肉系统，研究了模糊P+ID控制器的进化设计问题。气动肌肉的控制是一个具有挑战性的问题，因为他们的高度非线性，时变参数和不确定性。一个模糊P+ID控制器的构造使用增量模糊逻辑控制器的比例项在传统的PID控制器。几个控制器参数通过进化算法进行优化。优化是使用一个经常性的神经模糊动态模型的肌肉，而不是肌肉本身。控制结果，其中的控制目标是迫使肌肉长度遵循一个负载下的参考信号。经过进化设计后，在不需要进一步调整控制器参数的情况下，利用真实的肌肉获得了良好的跟踪性能。跟踪性能进行比较，另一种模糊控制器。
Abstract This paper studies the evolutionazy design of a fuzzy P+ID controller for an actual pneumatic muscle actuator system. The control of pneumatic muscles is a challenging problem because of their high degree of nonlineazity, time-varying parameters, and uncertainty. A fuzzy P+ID controller is constructed using an incremental fuzzy logic controller in place of the proportional term in a conventional PID controller. Several controller parameters are optimized via an evolutionary algorithm. The optimization is performed using a recurrent neuro-fuzzy dynamic model of the muscle rather than the muscle itself. Control results are presented, where the control objective is to force muscle length to follow a reference signal under a load. After evolutionary design, excellent tracking performance is obtained with the real muscle without the need for further tuning of controller pazameters. The tracking performance is compared to that of another fuzzy controller.