Fuzzy linearization for nonlinear systems: a preliminary study

Jin Yaochu, Zhu Jing, Jian Jingping
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引用次数: 5

Abstract

This paper proposes a novel control diagram for nonlinear systems, namely fuzzy linearization. On the basis of fuzzy reasoning, we build a set of fuzzy linear subsystems to linearize the original nonlinear system. Consequently, we design an optimal controller for every linear subsystem using the mature linear control theory. The control effect of each subsystem is composed via fuzzy reasoning to control the nonlinear system. Therefore, the design of any nonlinear systems can be simplified to the control problem of linear time-invariant systems. Compared to the existing methods such as the Taylor expansion and piecewise linearization, the proposed approach exhibits higher precision, better control performances and stronger robustness to system uncertainties.<>
非线性系统的模糊线性化:初步研究
本文提出了一种新的非线性系统控制图,即模糊线性化。在模糊推理的基础上,建立了一组模糊线性子系统,对原有的非线性系统进行线性化。因此,我们利用成熟的线性控制理论为每个线性子系统设计了最优控制器。通过模糊推理组合各子系统的控制效果,对非线性系统进行控制。因此,任何非线性系统的设计都可以简化为线性定常系统的控制问题。与Taylor展开和分段线性化等现有方法相比,该方法具有更高的精度、更好的控制性能和对系统不确定性更强的鲁棒性。
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