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Stable indirect adaptive switching control for fuzzy dynamical systems based on T-S multiple models

机译:基于T-S多重模型的模糊动力系统的稳定间接自适应切换控制。

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摘要

A new indirect adaptive switching fuzzy control method for fuzzy dynamical systems, based on Takagi-Sugeno (T-S) multiple models is proposed in this article. Motivated by the fact that indirect adaptive control techniques suffer from poor transient response, especially when the initialisation of the estimation model is highly inaccurate and the region of uncertainty for the plant parameters is very large, we present a fuzzy control method that utilises the advantages of multiple models strategy. The dynamical system is expressed using the T-S method in order to cope with the nonlinearities. T-S adaptive multiple models of the system to be controlled are constructed using different initial estimations for the parameters while one feedback linearisation controller corresponds to each model according to a specified reference model. The controller to be applied is determined at every time instant by the model which best approximates the plant using a switching rule with a suitable performance index. Lyapunov stability theory is used in order to obtain the adaptive law for the multiple models parameters, ensuring the asymptotic stability of the system while a modification in this law keeps the control input away from singularities. Also, by introducing the next best controller logic, we avoid possible infeasibilities in the control signal. Simulation results are presented, indicating the effectiveness and the advantages of the proposed method.
机译:本文提出了一种基于Takagi-Sugeno(T-S)多重模型的模糊动态系统间接自适应切换模糊控制方法。由于间接自适应控制技术会遭受较差的瞬态响应,特别是当估算模型的初始化非常不准确且工厂参数的不确定性区域很大时,我们提出了一种模糊控制方法,该方法利用了多模型策略。为了解决非线性问题,使用T-S方法表示动力系统。使用参数的不同初始估计值构造要控制系统的T-S自适应多个模型,而一个反馈线性化控制器根据指定的参考模型对应于每个模型。该模型将在每个时刻使用要确定的控制器,该模型使用具有适当性能指标的切换规则最近似于工厂。使用Lyapunov稳定性理论来获得多个模型参数的自适应定律,以确保系统的渐近稳定性,同时对该定律进行修改可使控制输入远离奇异点。同样,通过引入次佳的控制器逻辑,我们避免了控制信号中可能出现的不可行之处。仿真结果表明了该方法的有效性和优势。

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