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A receding horizon control approach to sampled-data implementation of continuous-time controllers
Authors:Dragan Ne&#x;i&#x;  Lars Grüne
Institution:aDepartment of Electrical and Electronic Engineering, The University of Melbourne, Victoria 3010, Australia;bMatematisches Institut, Universität Bayreuth, 95440, Germany
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, S. Tuna, Model predictive control: for want of a local control Lyapunov function, all is not lost, IEEE Trans. Automat. Control 2004, to appear] can be directly used for analysis of stability of our closed-loop system.
Keywords:Controller design  Stabilization  Sampled-data  Nonlinear  Receding horizon control  Model predictive control
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