Input and state constrained nonlinear predictive control: Application to a levitation system

The subject of the article concerns a constrained predictive control with feedback linearization (FBL) applied for multiple-input and multiple-output (MIMO) system. It relies on finding a compromise in every step between feasible and optimal linear quadratic (LQ) control by minimization of one variable. Behaviour of model signals in function of minimized variable is investigated, in order to assure the optimality of the solution. LQ control based applications for feedback linearized models do not meet the problem of choosing weights in linear quadratic cost function. That important problem is solved here by comparison of the cost function with that obtained for the linear approximated system in the operating point. That provides satisfactory behaviour and also justifies the simplified approach relied on minimization of only one variable for MIMO system.