Optimal robust control for generalized fuzzy dynamical systems: A novel use on fuzzy uncertainties

Jin Huang, Jiaguang Sun, Xibin Zhao, M. Gu
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Abstract

A novel approach for optimal robust control of a class of generalized fuzzy dynamical systems is proposed. This is a novel use of fuzzy uncertainty in doing dynamical system control. The system may have nonlinear nominal terms and the other terms with uncertainty, including unknown parameters and input disturbances. The Fuzzy sets theory is creatively employed in presenting the system parameter and input uncertainty, and then the control structure is deterministic (versus if-then rule-based as is typical in Mamdani-type fuzzy control). The desired controlled system performance is also deterministic, with guaranteed performances of uniform boundedness and uniform ultimate boundedness. Fuzzy informations on the uncertainties are used in searching optimal control gain under a proposed LQG-like quadratic cost index. The control gain design problem is formulated as a constrained optimization problem with the solution be proved to be always existed and unique. Systematic procedure is summarized for such control design.
广义模糊动力系统的最优鲁棒控制:模糊不确定性的新应用
提出了一类广义模糊动力系统最优鲁棒控制的新方法。这是模糊不确定性在动态系统控制中的一种新应用。系统可能具有非线性标称项和其他具有不确定性的项,包括未知参数和输入干扰。模糊集理论创造性地用于表示系统参数和输入的不确定性,然后控制结构是确定性的(相对于mamdani型模糊控制中典型的基于if-then规则的控制)。期望被控系统性能也是确定性的,具有一致有界性和一致最终有界性的保证性能。在提出的类lqg的二次代价指标下,利用不确定性的模糊信息搜索最优控制增益。将控制增益设计问题表述为一个约束优化问题,并证明其解总是存在且唯一。总结了这种控制设计的系统步骤。
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