Risk-Aware Stochastic MPC for Chance-Constrained Linear Systems

Risk-Aware Stochastic MPC for Chance-Constrained Linear Systems

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This paper presents a fully risk-aware model predictive control (MPC) framework for chance-constrained discrete-time linear control systems with process noise.Conditional value-at-risk (CVaR) as a popular coherent risk measure is incorporated in both the constraints and the cost function of the MPC framework.This allows the system to navigate Bosch PIE651BB1E Serie 4 59cm 4 Burners Induction Hob Touch Control Black the entire spectrum of risk assessments, from worst-case to risk-neutral scenarios, ensuring both constraint satisfaction and performance optimization in stochastic Refrigerator environments.The recursive feasibility and risk-aware exponential stability of the resulting risk-aware MPC are demonstrated through rigorous theoretical analysis by considering the disturbance feedback policy parameterization.In the end, two numerical examples are given to elucidate the efficacy of the proposed method.