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Continuous Stationarity Conditions for Hybrid System MPC Problems


A.B. Hempel

International Symposium on Mathematical Programming, Pittsburgh, PA

Recent results in inverse parametric optimization enable us to represent continuous piecewise-affine (PWA) dynamical systems as optimizing processes. This alternative description makes use of a convex decomposition of the PWA dynamics and can be used to represent the system dynamics without resorting to binary variables to encode the different regions. We exploit this new representation to cast Model Predictive Control problems as mathematical programs with complementarity constraints. The structure inherited from the construction of the optimizing process description leads to strong stationarity conditions for the solutions to these optimization problems. The results presented in this talk are joint work with Prof. Paul Goulart of Oxford University and Prof. John Lygeros.


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