12 citations · 36 across the 8 of their papers we have counts for
9 papers
Lower Bounds on the Worst-Case Complexity of Efficient Global Optimization
Wenjie Xu, Yuning Jiang, Emilio T. Maddalena +1
Efficient global optimization is a widely used method for optimizing expensive black-box functions such as tuning hyperparameter, and designing new material, etc. Despite its popul…
Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning
Loris Di Natale, Yingzhao Lian, Emilio T. Maddalena +2
This manuscript offers the perspective of experimentalists on a number of modern data-driven techniques: model predictive control relying on Gaussian processes, adaptive data-drive…
Experimental Data-Driven Model Predictive Control of a Hospital HVAC System During Regular Use
Emilio T. Maddalena, Silvio A. Muller, Rafael M. dos Santos +2
Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center. The ado…
Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach
Paul Scharnhorst, Emilio T. Maddalena, Yuning Jiang +1
The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalis…
KPC: Learning-Based Model Predictive Control with Deterministic Guarantees
Emilio T. Maddalena, Paul Scharnhorst, Yuning Jiang +1
We propose Kernel Predictive Control (KPC), a learning-based predictive control strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the unknown syst…
On the Optimality and Convergence Properties of the Iterative Learning Model Predictive Controller
Ugo Rosolia, Yingzhao Lian, Emilio T. Maddalena +2
In this technical note we analyse the performance improvement and optimality properties of the Learning Model Predictive Control (LMPC) strategy for linear deterministic systems. T…