Quasi-min-max MPC algorithms for LPV systems
An infinite horizon ``quasi min-max'' model predictive control (MPC) algorithm is developed. The plant is given by a polytopic linear discrete-time parameter varying (LPV) model. No mismatch exists between the model and the plant. The parameters and the state are assumed to be available in real time. The on-line optimization problems are solved by semi-definite programming involving linear matrix inequalities. At each sampling instance, the optimal control is calculated by minimizing the upper bound on the ``quasi-worst-case'' value of an infinite horizon quadratic objective function subject to constraints on inputs and outputs. It is shown that a receding horizon implementation of feasible solutions guarantees closed-loop stability. Numerical examples demonstrate the decreased conservatism, improved feasibility, and superior performance of the proposed MPC-LPV algorithm.
polytopic linear discrete-time parameter varying model
scientific article; zbMATH DE number 1437547