Optimal polytopic control system design

G.Z. Angelis, R. Kamidi, M.J.G. Molengraft, van de, H. Nijmeijer

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Polytopic linear models (PLM) are models with parameters that vary within a polytope of the model parameter space, where the vertices of the polytope are defined by the parameters of locally valid linear models. These PLMs are also known as fuzzy models, local model networks or multimodels. In this paper a novel regulator design method for PLM is suggested and formalized. Controller synthesis is based upon optimal control theory. It is shown that under controllability assumptions a solution exists to the Hamilton Jacobi Bellman (HJB) equation, which is known to be a sufficient condition for optimality of the closed loop system. An optimal static state feedback controller can then be computed as a solution of a convex optimization program. It turns out that the optimal control system has an infinite gain margin, a prerequisite for robustness of the control system. The controller design method is illustrated with an example
Original languageEnglish
Title of host publicationProceedings of the 15th IEEE international symposium on intelligent control : held jointly with the 8th IEEE Mediterranean conference on control and automation ; July 17-19, 2000, Rio Patras, Greece
EditorsP.P. Groumpos, N.T. Koussoulas, M. Polycarpou
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)0-7803-6491-0
Publication statusPublished - 2000


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