Set-based gain-scheduled control via quasi-convex difference inclusions
Corresponding Author
Antonio Sala
Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, Spain
Correspondence Antonio Sala, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Cno. Vera s/n, 46022 Valencia, Spain.
Email: [email protected]
Search for more papers by this authorCarlos Ariño
Department of Industrial Systems Engineering and Design, Universitat Jaume I, Castelló de la Plana, Spain
Search for more papers by this authorRuben Robles
Universidad Tecmilenio, Campus Las Torres, Monterrey, Mexico
Search for more papers by this authorCorresponding Author
Antonio Sala
Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, Spain
Correspondence Antonio Sala, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Cno. Vera s/n, 46022 Valencia, Spain.
Email: [email protected]
Search for more papers by this authorCarlos Ariño
Department of Industrial Systems Engineering and Design, Universitat Jaume I, Castelló de la Plana, Spain
Search for more papers by this authorRuben Robles
Universidad Tecmilenio, Campus Las Torres, Monterrey, Mexico
Search for more papers by this authorSummary
A nonlinear system with sector-bounded nonlinearities may be expressed as a quasi-linear parameter-varying (LPV) system (convex combination of linear models), being this a well-known fact. The convex difference inclusion (CDI) modeling framework proposed by Fiacchini and coworkers in several of their works generalizes the quasi-LPV modeling procedure and proposes robust controllers enlarging polytopic domain of attraction estimates. This works further generalizes the CDI approach to a gain-scheduled case including, also, some quasi-convex cases. Controller design is based on convexity properties of two set valued maps describing (with some uncertainty) the state evolution and the state-dependent set where scheduling variables take values. As most set-based approaches, the proposal is tractable in low-dimensional cases. The presented results encompass prior quasi-LPV and CDI models as particular cases.
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Special Issue:Emerging Approaches for Nonlinear Parameter Varying (NLPV) Systems
25 November 2021
Pages 8124-8146
