Intelligent Neural Sliding Control for Planetary Gear Type Inverted Pendulum Mechanism

Y. Huang, C. Hsu, T. Kuo, Jonqlan Lin
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引用次数: 3

Abstract

An intelligent neural sliding controller is developed for planetary train type inverted pendulum mechanism. The control methodology is based on the sliding mode control. The switching function in the normal control law is replaced with a bipolar sigmoid function. A fuzzy neural network is used to identify the pendulum dynamics. Adaptive tuning law is derived. The bipolar sigmoid function is thus adjusted according to the result of the identification process.
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行星齿轮式倒立摆机构的智能神经滑动控制
针对行星列式倒立摆机构,设计了一种智能神经滑动控制器。控制方法是基于滑模控制。将正常控制律中的开关函数替换为双极s型函数。采用模糊神经网络对摆动力学进行辨识。推导了自适应调谐律。因此,根据识别过程的结果调整双极s型函数。
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