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Hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems

机译：基于混合状态空间模糊模型的双速率采样混沌系统数字控制控制器

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摘要

We develop a hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems. A Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system and the extended parallel-distributed compensation technique is proposed and formulated for designing the fuzzy model-based controller under stability conditions. The optimal regional-pole assignment technique is also adopted in the design of the local feedback controllers for the multiple TS linear state-space models. The proposed design procedure is as follows: an equivalent fast-rate discrete-time state-space model of the continuous-time system is first constructed by using fuzzy inference systems. To obtain the continuous-time optimal state-feedback gains, the constructed discrete-time fuzzy system is then converted into a continuous-time system. The developed optimal continuous-time control law is finally converted into an equivalent slow-rate digital control law using the proposed intelligent digital redesign method. The main contribution of the paper is the development of a systematic and effective framework for fuzzy model-based controller design with dual-rate sampling for digital control of complex such as chaotic systems. The effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic Chua circuit.
机译：我们为混沌系统的数字控制开发了一种基于混合状态空间模糊模型的双速率采样控制器。利用Takagi-Sugeno（TS）模糊模型对混沌动力学系统进行建模，提出并推广了扩展的并行分布补偿技术，用于在稳定条件下设计基于模糊模型的控制器。在多个TS线性状态空间模型的局部反馈控制器的设计中，还采用了最佳区域极点分配技术。提出的设计过程如下：首先采用模糊推理系统建立了连续时间系统的等效快速离散时间状态空间模型。为了获得连续时间的最佳状态反馈增益，然后将构建的离散时间模糊系统转换为连续时间系统。最后，使用提出的智能数字重新设计方法，将开发的最优连续时间控制律转换为等效的慢速数字控制律。本文的主要贡献是开发了一种系统有效的框架，用于基于模糊模型的控制器设计，该模型具有双速率采样，可用于复杂系统（如混沌系统）的数字控制。通过对混沌Chua电路的数值模拟，证明了所提出的控制器设计方法的有效性和可行性。

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