H. Khati, H. Talem, Mohand Achour Touat, R. Mellah, S. Guermah
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引用次数: 0
Abstract
This paper presents the implementation of a Compensatory Adaptive Neuro-Fuzzy Inference System (CANFIS) controller to control an inverted pendulum. This controller is developed in order to readjust the parameters relating to the membership functions and the fuzzy rules used as well as to optimize the dynamics of the latter, using a learning algorithm based on the extended Kalman filter. The CANFIS controller is developed on the Simulink environment of the MATLAB software and is implemented on a Raspberry Pi 3 board, with a view to analyzing its real behavior, and testing its speed as well as its robustness through the use of the “Processor-In-the-Loop” (PIL) technique. The results obtained through PIL tests showed the effectiveness of the neuro-fuzzy controller equipped with a compensator.
提出了一种补偿自适应神经模糊推理系统(CANFIS)控制器来控制倒立摆。该控制器采用基于扩展卡尔曼滤波的学习算法，对隶属函数和模糊规则相关的参数进行调整，并对模糊规则进行动态优化。CANFIS控制器是在MATLAB软件的Simulink环境下开发的，并在Raspberry Pi 3板上实现，通过使用“Processor-In-the-Loop”(PIL)技术来分析其真实行为，并测试其速度和鲁棒性。通过PIL测试得到的结果表明，该神经模糊控制器具有补偿器的有效性。
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