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This paper focuses on the synthesis of nonlinear Model Predictive Controllers that can guarantee robustness with respect to measurement noise. The input-to-state stability framework is employed to analyze the robustness of the resulting Model Predictive Control (MPC) closed-loop system. It is illustrated how the obtained robustness result can be employed to synthesize asymptotically stabilizing observer-based...
In this note we show that robustness with respect to additive disturbances implies robustness with respect to state measurement errors and additive disturbances for a class of discrete-time closed-loop nonlinear systems. The main result is formulated in terms of input-to-state stability and includes the possible presence of input and state constraints. Moreover, the state feedback controllers are...
In this paper we present an asymptotically stabilizing output feedback control scheme for a class of nonlinear discrete-time systems. The presented scheme consists of an extended observer interconnected with an NMPC controller which represents a possible discontinuous state feedback control law. Local asymptotic stability of the resulting closed-loop system is proven
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