32 citations · 54 across the 20 of their papers we have counts for
20 papers
Smart energy management: process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems
Long Wu, Xunyuan Yin, Lei Pan +1
Integrated energy systems (IESs) are complex systems consisting of diverse operating units spanning multiple domains. To address its operational challenges, we propose a physics-in…
Iterative distributed moving horizon estimation of linear systems with penalties on both system disturbances and noise
Xiaojie Li, Song Bo, Yan Qin +1
In this paper, partition-based distributed state estimation of general linear systems is considered. A distributed moving horizon state estimation scheme is developed via decomposi…
Performance triggered adaptive model reduction for soil moisture estimation in precision irrigation
Sarupa Debnath, Bernard T. Agyeman, Soumya R. Sahoo +2
Accurate soil moisture information is crucial for developing precise irrigation control strategies to enhance water use efficiency. Soil moisture estimation based on limited soil m…
Reduced-order Koopman modeling and predictive control of nonlinear processes
Xuewen Zhang, Minghao Han, Xunyuan Yin
In this paper, we propose an efficient data-driven predictive control approach for general nonlinear processes based on a reduced-order Koopman operator. A Kalman-based sparse iden…
Large Language Models and Foundation Models in Smart Agriculture: Basics, Opportunities, and Challenges
Jiajia Li, Mingle Xu, Lirong Xiang +4
The past decade has witnessed the rapid development and adoption of ML & DL methodologies in agricultural systems, showcased by great successes in agricultural applications. Howeve…
Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control
Dong Chen, Kaixiang Zhang, Yongqiang Wang +3
Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs…
Extended Neighboring Extremal Optimal Control with State and Preview Perturbations
Amin Vahidi-Moghaddam, Kaixiang Zhang, Zhaojian Li +3
Optimal control schemes have achieved remarkable performance in numerous engineering applications. However, they typically require high computational cost, which has limited their…
Control invariant set enhanced safe reinforcement learning: improved sampling efficiency, guaranteed stability and robustness
Song Bo, Bernard T. Agyeman, Xunyuan Yin +1
Reinforcement learning (RL) is an area of significant research interest, and safe RL in particular is attracting attention due to its ability to handle safety-driven constraints th…
Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy
Long Wu, Xunyuan Yin, Lei Pan +1
The close integration of increasing operating units into an integrated energy system (IES) results in complex interconnections between these units. The strong dynamic interactions…
State estimation of a carbon capture process through POD model reduction and neural network approximation
Siyu Liu, Xunyuan Yin, Jinfeng Liu
This paper presents an efficient approach for state estimation of post-combustion CO2 capture plants (PCCPs) by using reduced-order neural network models. The method involves extra…
Control invariant set enhanced reinforcement learning for process control: improved sampling efficiency and guaranteed stability
Song Bo, Xunyuan Yin, Jinfeng Liu
Reinforcement learning (RL) is an area of significant research interest, and safe RL in particular is attracting attention due to its ability to handle safety-driven constraints th…
Sensor network design for post-combustion CO2 capture plants: economy, complexity and robustness
Siyu Liu, Xunyuan Yin, Jinfeng Liu
State estimation is crucial for the monitoring and control of post-combustion CO2 capture plants (PCCPs). The performance of state estimation is highly reliant on the configuration…
A Transferable Multi-stage Model with Cycling Discrepancy Learning for Lithium-ion Battery State of Health Estimation
Yan Qin, Chau Yuen, Xunyuan Yin +1
As a significant ingredient regarding health status, data-driven state-of-health (SOH) estimation has become dominant for lithium-ion batteries (LiBs). To handle data discrepancy a…
A sensitivity-based approach to optimal sensor selection for process networks
Siyu Liu, Xunyuan Yin, Zhichao Pan +1
Sensor selection is critical for state estimation, control and monitoring of nonlinear processes. However, evaluating the performance of each possible combination of out of …
Economic model predictive control of integrated energy systems: A multi-time-scale framework
Long Wu, Xunyuan Yin, Lei Pan +1
In this work, a composite economic model predictive control (CEMPC) is proposed for the optimal operation of a stand-alone integrated energy system (IES). Time-scale multiplicity e…
Distributed simultaneous state and parameter estimation of nonlinear systems
Siyu Liu, Xunyuan Yin, Jinfeng Liu +1
In this paper, we consider distributed simultaneous state and parameter estimation for a class of nonlinear systems, for which the augmented model comprising both the states and th…
Soil moisture map construction using microwave remote sensors and sequential data assimilation
Bernard T. Agyeman, Song Bo, Soumya R. Sahoo +3
Microwave remote sensors mounted on center pivot irrigation systems provide a feasible approach to obtain soil moisture information, in the form of water content maps, for the impl…
A consensus-based approach for parameter and state estimation of agro-hydrological system
Xunyuan Yin, Song Bo, Jinfeng Liu +1
The development of advanced closed-loop irrigation systems requires accurate soil moisture information. In this work, we address the problem of soil moisture estimation for the agr…
Cloud Resource Allocation for Cloud-Based Automotive Applications
Zhaojian Li, Tianshu Chu, Ilya V. Kolmanovsky +2
There is a rapidly growing interest in the use of cloud computing for automotive vehicles to facilitate computation and data intensive tasks. Efficient utilization of on-demand clo…
Cloud-Aided State Estimation of A Full-Car Semi-Active Suspension System
Lixian Zhang, Xunyuan Yin, Junnan Shen +1
In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to…