Receding horizon revisited: An easy way to robustly stabilize an LTV system
Systems & Control Letters
A receding-horizon regulator for nonlinear systems and a neural approximation
Automatica (Journal of IFAC)
Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Worst-case formulations of model predictive control for systems with bounded parameters
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief An improved approach for constrained robust model predictive control
Automatica (Journal of IFAC)
Characterization of the solution to a constrained H∞ optimal control problem
Automatica (Journal of IFAC)
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In this paper, we consider the problem of synthesizing robust state feedback control law for constrained uncertain LFT systems with bounded disturbance. A new Receding Horizon Control (RHC) scheme is proposed to achieve optimal H∞ performance over a finite horizon N. The cost is minimized over control policies and maximized over uncertainties and disturbances to yield a feedback control strategy. The control gains on the moving window will be used as decision variables to reduce conservatism and improve performance. Closed-loop stability and feasibility are guaranteed by introducing a terminal cost Vf and terminal constraint set Xf derived from off-line robust control. The RHC synthesis condition is formulated as a set of LMIs, which can be solved efficiently on-line.