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.
Efficient implementation of gaussian process–based predictive control by quadratic programming
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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.