A receding horizon control approach to sampled-data implementation of continuous-time controllers

L. Grüne, D. Nesic: A receding horizon control approach to sampled-data implementation of continuous-time controllers
Systems & Control Letters 55, 660 - 672, 2006

Smart-Link: http://www.elsevier.com/locate/sysconle
DOI: 10.1016/j.sysconle.2005.09.013
Keywords: controller design; stabilization; sampled-data; nonlinear; receding horizon control; model predictive control
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Abstract:

We propose a novel way for sampled-data implementation (with the zero order hold assumption) of continuous-time controllers for general nonlinear systems. We assume that a continuous-time controller has been designed so that the continuous-time closed-loop satisfies all performance requirements. Then, we use this control law indirectly to compute numerically a sampled-data controller. Our approach exploits a model predictive control (MPC) strategy that minimizes the mismatch between the solutions of the sampled-data model and the continuous-time closed-loop model. We propose a control law and present conditions under which stability and sub-optimality of the closed loop can be proved. We only consider the case of unconstrained MPC. We show that the recent results in [G.Grimm, M.J.Messina, A.R.Teel and S. Tuna, "Model predictive control: for want of a local control Lyapunov function, all is not lost", IEEE Trans. Automat. Contr. 50(2005), 546-558] can be directly used for analysis of stability of our closed-loop system.

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