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Sliding mode with neuro-fuzzy network controller for inverted pendulem

机译:具有神经模糊网络控制器的滑模用于倒立摆

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In this paper, we try to present a sliding mode with fuzzy-neural network controller for nonlinear systems. It is a special nonlinear control method (SMC) which has quick response, insensitive to parameters variation and disturbance. Online identification for plants is not needed, it's very suitable for nonlinear system control, but in reality using the chattering reduction and elimination are key problem in SMC. By using a function-augmented sliding hyper plane, it is guaranteed that the output tracking error converges to zero in finite time which can be set arbitrarily. The fuzzy-neural network mainly Self Tuning Fuzzy Inference System (STFIS) is used to approximate the unknown system functions and switch item. Finally, the sliding-mode with fuzzy-neural network control is used to control single inverted pendulum and confirms the validity of the proposals. Results of simulations containing tests of robustness are presented and realized in MATLAB environment.
机译:在本文中,我们尝试为非线性系统提出一种具有模糊神经网络控制器的滑模。这是一种特殊的非线性控制方法(SMC),具有快速响应,对参数变化和干扰不敏感。工厂不需要在线识别,它非常适合非线性系统控制,但实际上使用颤动的减少和消除是SMC中的关键问题。通过使用功能增强的滑动超平面,可以确保输出跟踪误差在有限时间内收敛到零,可以任意设置。模糊神经网络主要是自整定模糊推理系统(STFIS),用于近似未知系统的功能和切换项。最后,采用模糊神经网络控制的滑模控制单个倒立摆,验证了所提方法的有效性。给出了包含鲁棒性测试的仿真结果,并在MATLAB环境中实现。

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