Abstract
Model Predictive Control (MPC) with stability guarantees usually relies on terminal constraints; this not only increases computational complexity but might also compromise feasibility. Furthermore, a priori stability guarantees are often not available and the prediction horizon has to be set long enough to ensure the state is driven into the terminal region. In contrast, this paper presents analysis conditions to guarantee stability a priori for parameter dependent and nonlinear systems with no added constraints, using a Linear Parameter Varying (LPV) MPC control law. Stability is guaranteed using dissipativity arguments, given known conditions on the behavior of the nonlinearity arising from constrained MPC. When applied to nonlinear systems via quasi-LPV modeling, this result also gives a subset of the region of attraction, via the admissible set of parameters which can be mapped to a region in state space.
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