An off-line output feedback MPC strategy for nonlinear systems represented by quasi-LPV model^⁎

In case when a nonlinear system is represented by quasi-LPV model with bounded disturbance, we adopt the parameter-dependent dynamic output feedback MPC (PDDOFMPC) with guaranteed quadratic boundedness and physical constraints. We pre-specify one sequence of nested ellipsoids for estimated state, and another for estimation error, then calculate PDDOFMPC parameters for each combination of estimated state ellipsoid and estimation error ellipsoid. A look-up table is constructed off-line to store these controller parameters each related to a unique combination. On-line, the estimated state is iterated and the estimation error set is refreshed. By checking the smallest off-line estimated state ellipsoid to contain the real-time estimated state, and the smallest off-line estimation error ellipsoid to include the real-time estimation error set, a unique set of control parameters is taken from the look-up table at each sampling instant. An example is given to illustrate the effectiveness of the approach.