2012
DOI: 10.1109/tac.2012.2187400
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Explicit MPC for LPV Systems: Stability and Optimality

Abstract: Abstract-This paper considers high-speed control of constrained linear parameter-varying systems using model predictive control. Existing model predictive control schemes for control of constrained linear parameter-varying systems typically require the solution of a semi-definite program at each sampling instance. Recently, variants of explicit model predictive control were proposed for linear parameter-varying systems with polytopic representation, decreasing the online computational effort by orders of magni… Show more

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Cited by 113 publications
(88 citation statements)
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“…Nevertheless, some approaches using explicit MPC controllers [14] or MPC emulators [15] are reported for real-time control of PEMFC. Other relevant works such as [16] propose explicit MPC controllers for LPV systems, guaranteeing constraint satisfaction, recursive feasibility and asymptotic stability in simulation. These approaches avoid online optimization, but significantly increase the complexity of the controller compared with LPV techniques.…”
mentioning
confidence: 99%
“…Nevertheless, some approaches using explicit MPC controllers [14] or MPC emulators [15] are reported for real-time control of PEMFC. Other relevant works such as [16] propose explicit MPC controllers for LPV systems, guaranteeing constraint satisfaction, recursive feasibility and asymptotic stability in simulation. These approaches avoid online optimization, but significantly increase the complexity of the controller compared with LPV techniques.…”
mentioning
confidence: 99%
“…Another connection is the joint use of optimality and robust stability: this paper addresses set-membership state observation, but the dual(?) problem of constraint finite-time optimal control has also been the subject of recent works (Besselmann, Löfberg, & Morari, 2012). Much remains to be done to exploit these connections.…”
Section: Resultsmentioning
confidence: 99%
“…The noteworthy and unique characteristic of the MPC is that it can take the constraints on inputs, outputs, or state variables directly into account. Therefore, it has become a popular control method both in theory and practice [1].…”
Section: Introductionmentioning
confidence: 99%