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SSRN 2024年

作者： Ni, Chuantao Lang, Ziqiang Wang, Bing Li, Ang Cao, Chenxi Du, Wenli Qian, Feng Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Automatic Control and System Engineering University of Sheffield SheffieldS1 3JD United Kingdom

Source term estimation (STE) of hazardous gas leakages in chemical industrial parks (CIPs) is important for addressing environmental pollution and improving engineering safety and reliability. For this purpose, some least squares-based STE methods have recently been developed, which performs the real-time STE using an off-line determined response matrix that represents the relationship between the sensor measurements and strengths of hazardous gas leakages. However, these methods require the number and locations of potential hazardous gas leakage sources are known a priori, which is difficult in many practical applications. To resolve this issue, in the present study, a novel multi-sensor data-driven STE (MSDD-STE) approach is proposed, which overcomes the difficulties with existing least squares-based STE methods and can, for the first time, address the MSDD-STE problems in complicated scenarios where meteorological conditions such as wind directions change over a considerable range. A detailed analysis is introduced to evaluate the performance of the proposed approach. The effectiveness of the proposed approach is verified by comprehensive numerical simulation studies. © 2024, The Authors. All rights reserved.

关键词： Least squares approximations

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Data-Driven Distributionally Robust Mixed-Integer control through Lifted control Policy

arXiv

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arXiv 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China the Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China the Department of Mechanical Engineering University of Victoria VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. © 2025, CC BY.

关键词： Mixed-integer linear programming

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A Bayesian Approach to Total Least-Squares in Perturbed Compressive Sensing

SSRN

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SSRN 2024年

作者： Li, Junlin Sun, Weiwei Ding, Feng Lu, Renzhi School of Mathematics and Statistics Fuyang Normal University Fuyang236037 China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi214122 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

This paper introduces a Bayesian total least-squares (B-TLS) formulation to address the perturbedcompressive sensing problem. Due to the presence of a nonconvex nonseparable term, applying the traditional alternating minimization method to this formulation poses mathematical and computational challenges. To mitigate this problem, we develop a Bayesian proximal alternating linearized minimization (BPALM) method. In this method, every subproblem is characterized by convexity and yields solutions that are explicit and analytical. We further demonstrate the convergence of the proposed algorithm towards a stationary point of the objective function. Numerical experiments in sparse signal recovery are conducted to exhibit the proposed algorithm's effectiveness and superiority, focusing on its computational efficiency and estimation accuracy. © 2024, The Authors. All rights reserved.

关键词： Compressed sensing

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Robust Iterative Learning control Design for a Class of Uncertain Batch processes

Robust Iterative Learning Control Design for a Class of Unce...

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European control Conference (ECC)

作者： Robert Maniarski Wojciech Paszke Hongfeng Tao Eric Rogers Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi China School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper investigates the problem of designing robust iterative learning control laws for discrete-time batch processes with norm-bounded parameter uncertainties. A law of proportional-differential type is designed to achieve robust convergence of the tracking error in the batch-to-batch direction. It is shown that the design problem can be written as a two-dimensional system. Then, the recently developed non-conservative conditions for (structural) stability analysis for a linear Roesser model are used. The conditions for the existence and computation of the required control law matrices are linear matrix inequality-based. Finally, comparative simulation results show the effectiveness of the new design.

关键词： Uncertain systems Analytical models Simulation Computational modeling Batch production systems Europe Linear matrix inequalities

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Mobile observation for distributed parameter system with moving boundary over mobile sensor networks

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Journal of control and Decision 2021年第2期8卷 124-134页

作者： Jianzhong Zhang Baotong Cui Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan UniversityWuxiPeople’s Republic of China School of Internet of Things Engineering Jiangnan UniversityWuxi 214122People’s Republic of China School of Mathematics and Statistics Taishan UniversityTaian 271000People’s Republic of China

This paper considers the state observation for a class of distributed parameter systems(DPSs)with moving boundaries modelled by parabolic partial differential equations(PDEs).The method of mobile observation is presented to improve the observation performance of the systems and to eliminate the influence of moving boundaries on system observation with the aids of mobile sensor networks(MSNs).The MSNs which can move throughout the time-dependent spatial domain are used to provide the spatially averaged observations of the *** using the abstract evolution equation theory of parabolic PDEs and the Lyapunov stability arguments,a centralised observer is designed and a mobile control scheme for each of the mobile sensors is presented while taking account of the dynamics of the MSNs.A numerical example is finally presented to illustrate the effectiveness and the advantages of the proposed approach.

关键词： Distributed parameter system moving boundary abstract evolution equation state observation mobile sensor network

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids With Coupled Electricity-Hydrogen-Ammonia Under Uncertainties

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IEEE Transactions on Sustainable Energy 2025年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2025 IEEE.

关键词： Ammonia

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Event-Triggered SMC for Networked Markov Jumping Systems With Channel Fading and Applications: Genetic Algorithm

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IEEE Transactions on Cybernetics 2023年第10期53卷 6503-6515页

作者： Qi, Wenhai Zhang, Ning Zong, Guangdeng Su, Shun-Feng Yan, Huaicheng Yeh, Ruey-Huei Qufu Normal University School of Engineering Rizhao276826 China Chengdu University School of Information Science and Engineering Chengdu610106 China Tiangong University School of Control Science and Engineering Tianjin300387 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education Shanghai200237 China National Taiwan University of Science and Technology Department of Industrial Management Taipei106 Taiwan

The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jumping systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order to reduce resource consumption in the transmission process, an event-triggered protocol is adopted for networked MJSs. A key feature is that the signal transmission is inevitably affected by fading phenomenon due to delay, random noise, and amplitude attenuation in a networked environment. With the aid of a common sliding surface, an event-triggered SMC law is designed by adjusting the system network mode. Under the framework of stochastic Lyapunov stability, sufficient conditions are constructed to ensure the mean-square stability of the closed-loop networked MJSs, and the sliding region is reached around the specified sliding surface. Moreover, based on the iteration optimizing accessibility of objective function, an effective SMC approach under genetic algorithm is proposed to minimize the convergence region around the sliding surface. Finally, the effectiveness of the proposed method is proved by the F-404 aircraft model. © 2013 IEEE.

关键词： Markov processes

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Weakly supervised object detection with interactive edge attentive collaboration

Weakly supervised object detection with interactive edge att...

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Chinese control and Decision Conference, CCDC

作者： Wenlong Gao Ying Chen Yong Peng Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China School of Internet of Things Engineering Jiangnan University Wuxi China

ISBN: (纸本)9781665478977

Weakly supervised object detectors based on image-level annotation tend to overfit in the discriminative regions while ignoring the integrity of the object. In this paper, a novel weakly supervised object detection network with the interactive edge attentive collaboration module is proposed to alleviate the local optimal problem, in which edge attention is extracted as an object unity supervision for the detection, and a collaborative loss is introduced to enable VGG16 feature map with global attentive ability. The module can be detached from the network in the test period, which ensures the high efficiency of the detector without introducing any additional inference cost. Extensive experiments are carried out on the PASCAL VOC 2007 and VOC 2012 datasets, which reach 52.3% mAP, 67.7% CorLoc and 49.1% mAP, 68.0% CorLoc respectively, outperforming state-of-the-arts.

关键词： Costs Annotations Image edge detection Collaboration process control Object detection Detectors

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Implementing a modified Smith predictor using chemical reaction networks and its application to protein translation 4

Implementing a modified Smith predictor using chemical react...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Xiao, Yijun Lv, Hui Wang, Xing'an School of Software Engineering Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Liaoning Dalian116622 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110004 China College of Environmental and Chemical Engineering Dalian University Liaoning Dalian116622 China Dalian Chivy Biotechnology Co. Ltd Liaoning Dalian116622 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

In this article, a special attention is paid to the biochemical controller synthesis for time delay systems and try to implement the well-established Smith predictor approach in the context of biochemical systems. Then, chemical reaction networks (CRNs) are adopted to construct a modified Smith predictor scheme (integrating Smith predictor and feedback compensation controllers) for the first time. Taking a delayed protein translation model as the background, the CRNs-based proposed scheme has access to a method that can solve the effect of co-translated mRNA decay in protein translation. In addition, considering that the decay of mRNA affects mRNA stability and protein production, the co-translated mRNA degradation is treated as an interference input of the protein translation process. Our results show that the impact of a disturbance input (mRNA degradation) is restrained by the modified control strategy. The CRNs-based modified Smith predictor makes the protein translation process more robust and achieves protein output quickly and stably. © 2022 IEEE.

关键词： Time delay

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Numerical simulations and comparative analysis of two- and three-dimensional circulating fluidized bed reactors for CO2 capture

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Chinese Journal of chemical Engineering 2020年第12期28卷 2955-2967页

作者： Yefeng Zhou Yifan Han Yujian Lu Hongcun Bai Xiayi Hu Xincheng Zhang Fanghua Xie Xiao Luo Jingdai Wang Yongrong Yang National&Local United Engineering Research Centre for Chemical Process Simulation and Intensification Chemical Process Simulation and Optimization Engineering Research Center of Ministry of EducationXiangtan UniversityXiangtan 411105China State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering Ningxia UniversityYinchuan 750021China College of Chemistry and Chemical Engineering Hunan UniversityChangsha 410082China State Key Laboratory of Chemical Engineering College of Chemical and Biological EngineeringDepartment of Chemical EngineeringZhejiang UniversityHangzhou 310027China

Carbon dioxide(CO2),the main gas emitted from fossil burning,is the primary contributor to global *** fluidized bed reactor(CFBR)is proved as an energy-efficient method for post-combustion CO2 *** numerical simulation by computational fluid dynamics(CFD)is believed as a promising tool to study CO2 adsorption process in *** three-dimensional(3D)simulations were proved to have better predicting performance with the experimental results,two-dimensional(2D)simulations have been widely reported for qualitative and quantitative studies on gas-solid behavior in CFBR for its higher computational efficiency ***,the discrepancies between 2D and 3D simulations have rarely been evaluated by detailed *** that the differences between the 2D and 3D simulations will vary substantially with the changes of independent operating conditions,it is beneficial to lower computational costs to clarify the effects of dimensionality on the numerical CO2 adsorption runs under various operating *** this work,the comparative analysis for CO2 adsorption in 2D and 3D simulations was conducted to enlighten the effects of dimensionality on the hydrodynamics and reaction behaviors,in which the separation rate,species distribution and hydrodynamic characteristics were comparatively studied for both model *** both accuracy and computational costs considered,the viable suggestions were provided in selecting appropriate model frame for the studies on optimization of operating conditions,which directly affect the capture and energy efficiencies of cyclic CO2 capture process in CFBR.

关键词： Two-and three-dimensional simulations Circulating fluidized bed reactor Carbon dioxide adsorption Computational fluid dynamics Operating conditions

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