磁悬浮系统的qLPV建模与混合灵敏度L2控制

IF 2.4 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS
L. B. D. E. Rosa, M. S. Oliveira, Renan Lima Pereira
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引用次数: 1

摘要

摘要本文提出了一种用于实验磁悬浮系统的综合混合灵敏度控制设计。该控制策略可以被视为使用线性分数表示(LFR)的离散时间线性参数变化(LPV)系统的环路成形过程的扩展。通过使用以线性矩阵不等式(LMI)形式给出的有效的二次方法,实现了一种具有计算吸引力的函数增益调度技术。尽管获得控制器需要严格的数学考虑,但其实际实现指南是作为一种使用LMI的直接方法提出的。对Quanser制造的磁悬浮设备进行了详细的建模,以说明该过程,包括描述非线性方程嵌入过程,以获得离散准LPV(qLPV)模型。实验结果证明了所提出的控制设计的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
qLPV modeling and mixed-sensitivity L 2 control for a magnetic levitation system
ABSTRACT This paper proposes a comprehensive mixed-sensitivity control design for an experimental magnetic levitation (Maglev) system. The control strategy can be seen as an extension of the loop-shaping procedure for discrete-time linear parameter-varying (LPV) systems using linear-fractional representation (LFR). By making use of an efficient quadratic approach given in the form of linear matrix inequalities (LMIs), a functional and computationally attractive gain-scheduling technique is achieved. Despite the rigorous mathematical considerations to obtain the controller, the guidelines to its practical implementation are presented as a straightforward method using LMIs. A detailed modeling of the Maglev plant manufactured by Quanser is carried out to illustrate the procedure, including a description of the nonlinear equations embedding process to obtain a discretized quasi-LPV (qLPV) model. Experimental results demonstrate the effectiveness of the proposed control design.
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来源期刊
International Journal of General Systems
International Journal of General Systems 工程技术-计算机:理论方法
CiteScore
4.10
自引率
20.00%
发文量
38
审稿时长
6 months
期刊介绍: International Journal of General Systems is a periodical devoted primarily to the publication of original research contributions to system science, basic as well as applied. However, relevant survey articles, invited book reviews, bibliographies, and letters to the editor are also published. The principal aim of the journal is to promote original systems ideas (concepts, principles, methods, theoretical or experimental results, etc.) that are broadly applicable to various kinds of systems. The term “general system” in the name of the journal is intended to indicate this aim–the orientation to systems ideas that have a general applicability. Typical subject areas covered by the journal include: uncertainty and randomness; fuzziness and imprecision; information; complexity; inductive and deductive reasoning about systems; learning; systems analysis and design; and theoretical as well as experimental knowledge regarding various categories of systems. Submitted research must be well presented and must clearly state the contribution and novelty. Manuscripts dealing with particular kinds of systems which lack general applicability across a broad range of systems should be sent to journals specializing in the respective topics.
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