توضیحات
ABSTRACT
This paper presents a number of state feedback controller design methods for fuzzy dynamic systems with H¥ optimization and/or additional constraints on the closed-loop pole location. The controller design involves solving a set of linear matrix inequalities and the control laws are numerically tractable via LMI techniques. The global stability of the closedloop fuzzy control system is also established.
INTRODUCTION
During the last few years, a number of papers have been presented to deal with the problem of systematic analysis and design of fuzzy logic controllers for fuzzy dynamic systems; see (Cao et al. 1996, 1997a, 1997b, Feng et al. 1996, Han and Feng 1998) for example. The design methods can be stated as follows: to represent a nonlinear system as a family of local linear models smoothly connected through fuzzy membership functions such that the control law for each local model can be designed by using linear control system theory, and then to construct a global controller from the local controllers in such a way that global stability of the closed loop fuzzy control system is guaranteed. While many papers deal with stability analysis of the fuzzy system, only a few papers consider the performance design. Moreover, those papers on this topic deal mostly with the H ¥ optimization techniques (Feng et al. 1996, Tanaka et al. 1996, Han and Feng 1998), and provide little control over the transient behavior and closed-loop pole locations. It is believed that the difficulty lies in modifying the algebraic Riccati equations to enforce specific root-clustering objectives. It has been noticed recently that fuzzy control synthesis can be formulated as a convex optimization problem involving linear matrix inequalities (LMI) which correspond to its counterpart of the usual Riccati equations (Tanaka et al.1996, Han and Feng 1998). Because LMIs intrinsically reflect constraints rather than optimality, they have been introduced to offer more flexibility for combining several constraints on the closed-loop system (Body et al. 1994, Chilali and Gahinet 1994, 1996, Apkarian et al. 1996 ). Moreover, many efficient optimization algorithms and softwares are now available to solve LMIs in a fast way (Gahinet et al. 1995, Apkarian et al. 1996).
Year: 2016
Publisher : Department of Electrical Engineering
By : Z.X. Han , G. Feng , B.L. Walcott and Y.M. Zhang
File Information: English Language/ 22 Page / size: 97 KB
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سال : 2016
ناشر : Department of Electrical Engineering
کاری از : Z.X. Han , G. Feng , B.L. Walcott and Y.M. Zhang
اطلاعات فایل : زبان انگلیسی / 22 صفحه / حجم : KB 97
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