31 citations · 91 across the 19 of their papers we have counts for
19 papers
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…
Hypergraph-Based Fast Distributed AC Power Flow Optimization
Xinliang Dai, Yingzhao Lian, Yuning Jiang +2
This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication str…
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…
Robustly Learning Regions of Attraction from Fixed Data
Matteo Tacchi, Yingzhao Lian, Colin Jones
While stability analysis is a mainstay for control science, especially computing regions of attraction of equilibrium points, until recently most stability analysis tools always re…
Fault Detection via Occupation Kernel Principal Component Analysis
Zachary Morrison, Benjamin P. Russo, Yingzhao Lian +1
The reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamical system. While traditional model-based methods have been…
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…
Distributed data-driven predictive control for cooperatively smoothing mixed traffic flow
Jiawei Wang, Yingzhao Lian, Yuning Jiang +3
Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data-dri…
Scheduling Delays and Curtailment for Household Appliances with Deterministic Load Profiles using MPC
Yingzhao Lian, Yuning Jiang, Colin N. Jones +1
Smart home appliances can time-shift and curtail their power demand to assist demand side management or allow operation with limited power, as in an off-grid application. This pape…
A Proximal-Point Lagrangian Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control
Yingzhao Lian, Yuning Jiang, Daniel F. Opila +1
Nonlinear model predictive control has been widely adopted to manipulate bilinear systems with dynamics that include products of the inputs and the states. These systems are ubiqui…
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…
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…
Are Investors Biased Against Women? Analyzing How Gender Affects Startup Funding in Europe
Michael Färber, Alexander Klein
One of the main challenges of startups is to raise capital from investors. For startup founders, it is therefore crucial to know whether investors have a bias against women as star…
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…
Resource-Aware Stochastic Self-Triggered Model Predictive Control
Yingzhao Lian, Yuning Jiang, Naomi Stricker +2
This paper considers the control of uncertain systems that are operated under limited resource factors, such as battery life or hardware longevity. We consider here resource-aware…
From System Level Synthesis to Robust Closed-loop Data-enabled Predictive Control
Yinghao Lian, Colin N. Jones
Willems' fundamental lemma and system level synthesis both characterize a linear dynamic system by its input/output sequences. In this work, we extend the application of the fundam…
Koopman based data-driven predictive control
Yingzhao Lian, Renzi Wang, Colin N. Jones
Sparked by the Willems' fundamental lemma, a class of data-driven control methods has been developed for LTI systems. At the same time, the Koopman operator theory attempts to cast…
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…
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…
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,…