Nonlinear systems analysis (2nd ed.)
Nonlinear systems analysis (2nd ed.)
On the stabilizing property of SIORHC
Automatica (Journal of IFAC)
SIAM Review
Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Determinant Maximization with Linear Matrix Inequality Constraints
SIAM Journal on Matrix Analysis and Applications
An efficient model predictive controller with pole placement
Information Sciences: an International Journal
Delayed Perturbation Bounds for Receding Horizon Controls
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Technical Communique: Who needs QP for linear MPC anyway?
Automatica (Journal of IFAC)
Brief An improved approach for constrained robust model predictive control
Automatica (Journal of IFAC)
Brief Optimizing the end-point state-weighting matrix in model-based predictive control
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief Implementation of stabilizing receding horizon controls for time-varying systems
Automatica (Journal of IFAC)
Constrained RHC for LPV systems with bounded rates of parameter variations
Automatica (Journal of IFAC)
Constrained linear MPC with time-varying terminal cost using convex combinations
Automatica (Journal of IFAC)
Hi-index | 22.16 |
In this paper, a new stabilizing receding horizon control, based on a finite input and state horizon cost with a finite terminal weighting matrix, is proposed for time-varying discrete linear systems with constraints. We propose matrix inequality conditions on the terminal weighting matrix under which closed-loop stability is guaranteed for both cases of unconstrained and constrained systems with input and state constraints. We show that such a terminal weighting matrix can be obtained by solving a linear matrix inequality (LMI). In the case of constrained time-invariant systems, an artificial invariant ellipsoid constraint is introduced in order to relax the conventional terminal equality constraint and to handle constraints. Using the invariant ellipsoid constraints, a feasibility condition of the optimization problem is presented and a region of attraction is characterized for constrained systems with the proposed receding horizon control.