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Adaptive Model Predictive Control by Learning Classifiers
Stochastic model predictive control has been a successful and robust control framework for many robotics tasks where the system dynamics model is slightly inaccurate or in the presence of environment disturbances.
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty
We propose an adaptive optimisation approach for tuning stochastic model predictive control (MPC) hyper-parameters while jointly estimating probability distributions of the transition model parameters based on performance rewards.
Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control
Model predictive control (MPC) has been successful in applications involving the control of complex physical systems.
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