Input-to-state Stabilizing Sub-optimal Nonlinear Mpc Algorithms with an Application to Dc-dc Converters
نویسندگان
چکیده
This paper focuses on the synthesis of computationally friendly sub-optimal nonlinear Model Predictive Control (MPC) algorithms with guaranteed robust stability. The input-to-state stability framework is employed to analyze the robustness of the resulting MPC closed-loop systems. Two new sub-optimal nonlinear MPC schemes are proposed, based on a contraction argument and an artificial Lyapunov function, respectively. The developed theory is illustrated by applying it to control a Buck-Boost DC-DC converter. Copyright c ©2006 IFAC
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تاریخ انتشار 2006