Risk-Aware Model Predictive Control Enabled by Bayesian Learning
Proposed a risk-averse Model Predictive Control (MPC) framework, which estimates the underlying parameter distribution using online Bayesian learning and derived a risk-averse control policy by reformulating classical MPC problems as Bayesian risk optimization (BRO) problems.
Bayesian Learning Model Predictive Control for Process-aware Source Seeking
Proposed a Bayesian learning based MPC approach to solve the process-aware source seeking (PASS) problem, which combines the objectives of optimal search and source seeking and aims to utilize the exploration and detection information to guide the process of source seeking.