activity
20192025
most citedOne for Many: Transfer Learning for Building HVAC Control

57 citations · 110 across the 22 of their papers we have counts for

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7 papers · 1 filter

eess.SY2023

POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems

Yixuan Wang, Weichao Zhou, Jiameng Fan +6

Neural networks (NNs) playing the role of controllers have demonstrated impressive empirical performances on challenging control problems. However, the potential adoption of NN con…

eess.SY2022★ 8 cited

Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments

Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao +6

It is quite challenging to ensure the safety of reinforcement learning (RL) agents in an unknown and stochastic environment under hard constraints that require the system state not…

eess.SY2021★ 5 cited

Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees

Yixuan Wang, Chao Huang, Zhaoran Wang +2

In the current control design of safety-critical autonomous systems, formal verification techniques are typically applied after the controller is designed to evaluate whether the r…

eess.SY2021★ 1 cited

Learning-based Framework for Sensor Fault-Tolerant Building HVAC Control with Model-assisted Learning

Shichao Xu, Yangyang Fu, Yixuan Wang +2

As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort a…

eess.SY2021★ 1 cited

Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation

Yixuan Wang, Chao Huang, Zhilu Wang +3

Neural networks are being increasingly applied to control and decision-making for learning-enabled cyber-physical systems (LE-CPSs). They have shown promising performance without r…

eess.SY2020★ 21 cited

Energy-Efficient Control Adaptation with Safety Guarantees for Learning-Enabled Cyber-Physical Systems

Yixuan Wang, Chao Huang, Qi Zhu

Neural networks have been increasingly applied for control in learning-enabled cyber-physical systems (LE-CPSs) and demonstrated great promises in improving system performance and…

eess.SY2020★ 57 cited

One for Many: Transfer Learning for Building HVAC Control

Shichao Xu, Yixuan Wang, Yanzhi Wang +2

The design of building heating, ventilation, and air conditioning (HVAC) system is critically important, as it accounts for around half of building energy consumption and directly…