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作 者:Liu Fuchun Yao Yu He Fenahua
机构地区:[1]Control and Simulation Center, Harbin Inst. of Technology, Harbin 150001, P. R. China [2]Coll. of Automation Science and Engineering, South China Univ. of Technology, Guangzhou 510640, P. R. China
出 处:《Journal of Systems Engineering and Electronics》2009年第2期371-378,共8页系统工程与电子技术(英文版)
基 金:supported by the National Natural Science Foundation of China (60574004; 60736024; 60674043) ;the Key Project of Science and Technology Research of the Ministry of Education of China (708069).
摘 要:This article investigates the problem of robust H∞ controller design for sampled-data systems with time-varying norm-bounded parameter uncertainties in the state matrices. Attention is focused on the design of a causal sampled-data controller, which guarantees the asymptotical stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed H∞ performance bound for all admissible uncertainties. Sufficient condition for the solvability of the problem is established in terms of linear matrix inequalities (LMIs). It is shown that the desired H∞ controller can be constructed by solving certain LMIs. An illustrative example is given to demonstrate the effectiveness of the proposed method.This article investigates the problem of robust H∞ controller design for sampled-data systems with time-varying norm-bounded parameter uncertainties in the state matrices. Attention is focused on the design of a causal sampled-data controller, which guarantees the asymptotical stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed H∞ performance bound for all admissible uncertainties. Sufficient condition for the solvability of the problem is established in terms of linear matrix inequalities (LMIs). It is shown that the desired H∞ controller can be constructed by solving certain LMIs. An illustrative example is given to demonstrate the effectiveness of the proposed method.
关 键 词:H∞ control sampled-data systems uncertain systems linear matrix inequality
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