A robust adaptive MPC framework for nonlinear systems with bounded disturbances uses Gaussian process models and contraction metrics to guarantee recursive feasibility, robust constraint satisfaction, and convergence with high probability.
Cautious model predictive control using gaussian process regression
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A robust and adaptive MPC formulation for Gaussian process models
A robust adaptive MPC framework for nonlinear systems with bounded disturbances uses Gaussian process models and contraction metrics to guarantee recursive feasibility, robust constraint satisfaction, and convergence with high probability.