New robust model predictive control for uncertain systems with input constraints using relaxation matrices

作者：Lee S M; Won S C; Park J H^*

来源：Journal of Optimization Theory and Applications, 2008, 138(2): 221-234.

DOI：10.1007/s10957-008-9375-5

• model predictive control
• time-varying uncertain systems
• input constraints
• LMIs

In this paper, we propose a new robust model predictive control (MPC) method for time-varying uncertain systems with input constraints. We formulate the problem as a minimization of the worst-case finite-horizon cost function subject to a new sufficient condition for cost monotonicity. The proposed MPC technique uses relaxation matrices to derive a less conservative terminal inequality condition. The relaxation matrices improve feasibility and system performance. The optimization problem is solved by semidefinite programming involving linear matrix inequalities (LMIs). A numerical example shows the effectiveness of the proposed method.

• 出版日期2008-8