A synthesis approach for output feedback robust constrained model predictive control

A synthesis approach for output feedback robust model predictive control based-on input–output model

“…Hence, according to Theorem 1, (19) guarantees quadratic boundedness of (9). When w(k) = 0 for all k ≥ 0, by applying (16) and (13), it is shown that is an upper bound of…”

“…The technique of QB (see [1,2]) can be used directly on (9). In [10], the technique of QB is firstly applied to the output feedback robust MPC for the state space model (the MPC technique has been further improved in [5,8]).…”

“…For a real process, the state is usually unmeasurable so that the output feedback control should be considered. With respect to the output feedback MPC based-on the state estimator, for a system with bounded disturbance without model parametric uncertainty, one can refer to [17,24,13], for that with model parametric uncertainty without disturbance, to [14], and for that with both model parametric uncertainty and bounded disturbance, to [5,9,8].…”

Robust Model Predictive Control Design

“…The main idea of (Kothare et al, 1996) is the use of infinite horizon control laws which guarantee robust stability for state feedback. In (Ding et al, 2008) output feedback robust MPC for systems with both polytopic and bounded uncertainty with input/state constraints is presented. Off-line, it calculates a sequence of output feedback laws based on the state estimators, by solving LMI optimization problem.…”

Robust Model Predictive Controller Design: Finite and Infinite Horizon

“…Numerous design procedures were developed to guarantee robust stability. They are based on the infinite prediction or optimization horizon with the on-line LMI optimization [Kothare et al, 1996], the min-max optimization with a terminal constraint in an invariant set Mayne, 1998, Lofberg, 2003], the off-line LMI optimization to calculate a sequence of output feedback laws and the on-line selection of the appropriate law [Ding et al, 2008] or the robust tube-based control design approach [Mayne et al, 2005]. The problems of the computational complexity and the robust stability are solved in the robust explicit MPC [Kerrigan and Maciejowski, 2004].…”