Abstract: Bayesian optimization (BO) is a popular method for solving expensive black-box problems. However, when the dimension of the problem increases, the performance of BO decreases dramatically.
Abstract: Current data-driven predictive control (DDPC) methods heavily rely on data collected in open-loop operation with elaborate design of inputs. However, due to safety or economic concerns, ...
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