12 citations · 36 across the 5 of their papers we have counts for
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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…
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…
NSM Converges to a k-NN Regressor Under Loose Lipschitz Estimates
Emilio T. Maddalena, Colin N. Jones
Although it is known that having accurate Lipschitz estimates is essential for certain models to deliver good predictive performance, refining this constant in practice can be a di…
A Neural Network Architecture to Learn Explicit MPC Controllers from Data
E. T. Maddalena, C. G. da S. Moraes, G. Waltrich +1
We present a methodology to learn explicit Model Predictive Control (eMPC) laws from sample data points with tunable complexity. The learning process is cast in a special Neural Ne…