38 citations · 73 across the 24 of their papers we have counts for
22 papers · 1 filter
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…
Robust MPC with Zone Tracking
Zhiyinan Huang, Jinfeng Liu, Biao Huang
We propose a robust nonlinear model predictive control design with generalized zone tracking (ZMPC) in this work. The proposed ZMPC has guaranteed convergence into the target zone…
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 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…
Computing control invariant sets of nonlinear systems: decomposition and distributed computing
Benjamin Decardi-Nelson, Jinfeng Liu
In this work, we present a distributed framework based on the graph algorithm for computing control invariant set for nonlinear cascade systems. The proposed algorithm exploits the…
Model predictive control of agro-hydrological systems based on a two-layer neural network modeling framework
Zhiyinan Huang, Jinfeng Liu, Biao Huang
Water scarcity is an urgent issue to be resolved and improving irrigation water-use efficiency through closed-loop control is essential. The complex agro-hydrological system dynami…
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…
Sensitivity-based dynamic performance assessment for model predictive control with Gaussian noise
Jiangbang Liu, Song Bo, Benjamin Decardi-Nelson +3
Economic model predictive control and tracking model predictive control are two popular advanced process control strategies used in various of fields. Nevertheless, which one shoul…
Robust economic MPC of the absorption column in post-combustion carbon capture through zone tracking
Benjamin Decardi-Nelson, Jinfeng Liu
Several studies have reported the importance of optimally operating the absorption column in a post-combustion CO2 capture (PCC) plant. It has been demonstrated in our previous wor…
Adaptive model reduction and state estimation of agro-hydrological systems
Soumya R. Sahoo, Jinfeng Liu
Closed-loop irrigation can deliver a promising solution for precision irrigation. The accurate soil moisture (state) estimation is critical in implementing the closed-loop irrigati…
Knowledge-based optimal irrigation scheduling of agro-hydrological systems
Soumya R. Sahoo, Bernard T. Agyeman, Sarupa Debnath +1
The typical agricultural irrigation scheduler provides information on how much to irrigate and when to irrigate. The accurate and effective scheduler decision for a large agricultu…
LSTM-based model predictive control with discrete inputs for irrigation scheduling
Bernard T. Agyeman, Soumya R. Sahoo, Jinfeng Liu +1
The development of well-devised irrigation scheduling methods is desirable from the perspectives of plant quality and water conservation. In this article, a model predictive contro…
Subsystem decomposition and state estimation of nonlinear processes with implicit time-scale multiplicity
Sarupa Debnath, Soumya Ranjan Sahoo, Benjamin Decardi-Nelson +1
In this work, we propose a subsystem decomposition approach and a distributed estimation scheme for a class of implicit two-time-scale nonlinear systems. Taking the advantage of th…
Robust economic model predictive control with zone tracking
Benjamin Decardi-Nelson, Jinfeng Liu
This paper presents a robust economic model predictive control (EMPC) formulation with zone tracking for discrete-time uncertain nonlinear systems. The proposed design ensures that…
A comparative study of model approximation methods applied to economic MPC
Zhiyinan Huang, Qinyao Liu, Jinfeng Liu +1
Economic model predictive control (EMPC) has attracted significant attention in recent years and is recognized as a promising advanced process control method for the next generatio…
Computing robust control invariant sets of constrained nonlinear systems: A graph algorithm approach
Benjamin Decardi-Nelson, Jinfeng Liu
This paper deals with the computation of the largest robust control invariant sets (RCISs) of constrained nonlinear systems. The proposed approach is based on casting the search fo…
Simultaneous state and parameter estimation: the role of sensitivity analysis
Jianbang Liu, Aristarchus Gnanasekar, Yi Zhang +4
State and parameter estimation is essential for process monitoring and control. Observability plays an important role in both state and parameter estimation. In simultaneous state…
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…