activity
20202026
most citedAdaptive Robust Data-driven Building Control via Bi-level Reformulation: an Experimental Result

20 citations · 52 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CV2026

TempoKV: Predictive KV Cache Quantization for Autoregressive Video Generation

Jiahui Hu, Weile Mo, Peiliang Cai +5

Autoregressive (AR) video diffusion models enable streaming generation of long videos but suffer from significant memory overhead due to the rapidly growing KV cache. Existing KV c…

eess.SY2026

User-specified Kelvin-hour budgets within model predictive control for energy-efficient buildings: Simulation and field demonstration

Jicheng Shi, Colin N. Jones

For energy-efficient building control, model predictive control (MPC) has been widely proposed to reduce energy use while maintaining prescribed indoor temperature bounds. In pract…

eess.SY2025

Personalized Building Climate Control with Contextual Preferential Bayesian Optimization

Wenbin Wang, Jicheng Shi, Colin N. Jones

Efficient tuning of building climate controllers to optimize occupant utility is essential for ensuring overall comfort and satisfaction. However, this is a challenging task since…

math.OC2025

Distributionally Robust System Level Synthesis With Output Feedback Affine Control Policy

Yun Li, Jicheng Shi, Colin N. Jones +2

This paper studies the finite-horizon robust optimal control of constrained linear systems subject to model mismatch and additive stochastic disturbances. Utilizing the system leve…

eess.SY2025

Model Predictive Building Climate Control for Mitigating Heat Pump Noise Pollution (Extended Version)

Yun Li, Jicheng Shi, Colin N. Jones +2

Noise pollution from heat pumps (HPs) has been an emerging concern to their broader adoption, especially in densely populated areas. This paper explores a model predictive control…

eess.SY2025

Disturbance-adaptive Model Predictive Control for Bounded Average Constraint Violations

Jicheng Shi, Colin N. Jones

This paper considers stochastic linear time-invariant systems subject to constraints on the average number of state-constraint violations over time without knowing the disturbance…

eess.SY2025

What price to pay? Auto-tuning a building MPC controller for optimal economic cost

Jiarui Yu, Jicheng Shi, Wenjie Xu +1

Demand-side management (DSM) programs introduce complex pricing, requiring advanced control for cost minimization. Model Predictive Control (MPC) offers a solution but its performa…

eess.SY2024★ 1 cited

Disturbance-Adaptive Data-Driven Predictive Control: Trading Comfort Violations for Savings in Building Climate Control

Jicheng Shi, Christophe Salzmann, Colin N. Jones

Model Predictive Control (MPC) has demonstrated significant potential in improving energy efficiency in building climate control, outperforming traditional controllers commonly use…

eess.SY2023

Efficient Recursive Data-enabled Predictive Control (Extended Version)

Jicheng Shi, Yingzhao Lian, Colin N. Jones

In the field of model predictive control, Data-enabled Predictive Control (DeePC) offers direct predictive control, bypassing traditional modeling. However, challenges emerge with…

eess.SY2023★ 3 cited

Adaptive Data-Driven Prediction in a Building Control Hierarchy: A Case Study of Demand Response in Switzerland

Jicheng Shi, Yingzhao Lian, Christophe Salzmann +1

By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectivel…

eess.SY2023★ 5 cited

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-based Filters

Yingzhao Lian, Jicheng Shi, Colin N. Jones

(Extended Version) Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency bet…

eess.SY2022★ 7 cited

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…

eess.SY2022★ 16 cited

Data-driven input reconstruction and experimental validation

Jicheng Shi, Yingzhao Lian, Colin N. Jones

This paper addresses a data-driven input reconstruction problem based on Willems' Fundamental Lemma in which unknown input estimators (UIEs) are constructed directly from historica…

eess.SY2021★ 20 cited

Adaptive Robust Data-driven Building Control via Bi-level Reformulation: an Experimental Result

Yingzhao Lian, Jicheng Shi, Manuel Koch +1

Data-driven control approaches for the minimization of energy consumption of buildings have the potential to significantly reduce deployment costs and increase uptake of advanced c…

eess.SY2020

Robust Learning Model Predictive Control for Periodically Correlated Building Control

Jicheng Shi, Yingzhao Lian, Colin N. Jones

Accounting for more than 40% of global energy consumption, residential and commercial buildings will be key players in any future green energy systems. To fully exploit their poten…

eess.SY2020

Towards an Unified Structure for Reinforcement Learning: an Optimization Approach

Jicheng Shi, Yingzhao Lian, Colin N. Jones

Both the optimal value function and the optimal policy can be used to model an optimal controller based on the duality established by the Bellman equation. Even with this duality,…