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Stabilization of Nonlinear Systems Using Sampled-Data Output-Feedback Fuzzy Controller Based on Polynomial-Fuzzy-Model-Based Control Approach

机译:基于多项式-模糊模型的控制方法基于采样数据输出-反馈模糊控制器的非线性系统镇定

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This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.
机译:本文研究了基于采样数据输出反馈(SDOF)多项式模糊模型的控制系统的稳定性。用多项式模糊模型表示非线性工厂,提出了一种SDOF模糊控制器,利用系统输出信息进行控制。由于仅系统输出可用于反馈补偿,因此与全状态反馈情况相比,控制器设计和系统分析更具挑战性。此外,由于采样活动,控制信号在采样期间通过零阶保持保持恒定,这使系统动力学复杂化,并且使稳定性分析更加困难。在本文中,考虑了两种情况的SDOF模糊控制器,它们共享或不共享相同数量的模糊规则。基于Lyapunov稳定性理论,使用平方和(SOS)方法研究系统稳定性。获得了基于SOS的稳定性条件,以保证系统的稳定性并合成SDOF模糊控制器。仿真例子说明了所提出的SDOF模糊控制方法的优点。

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