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On strong structural controllability and observability of linear time-varying systems: a constructive method

Science China(information Sciences) 2019年第1期62卷 134-147页

作者： Shaoyuan LI Jianbin MU Yishi WANG Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

In this paper, we consider the controllability and observability of generalized linear time-varying(LTV) systems whose coefficients are not exactly known. All that is known about these systems is the placement of non-zero entries in their coefficient matrices(A, B). We provide the characterizations in order to judge whether the placements can guarantee the controllability/observability of such LTV systems, regardless of the exact value of each non-zero coefficient. We also present a direct and efficient algorithm with an associated time cost of O (n+m+ν) to verify the conditions of our characterizations, where n and m denote the number of columns of A and B, respectively, and ν is number of non-zero entries in(A, B).

关键词： linear time-varying(LTV) systems strong structural properties controllability observability duality

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SOCIAL LEARNING WITH TIME-VARYING WEIGHTS

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Journal of systems Science & Complexity 2014年第3期27卷 581-593页

作者： LIU Qipeng FANG Aili WANG Lin WANG Xiaofan Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This paper investigates a non-Bayesian social learning model, in which each individual updates her beliefs based on private signals as well as her neighbors＇ beliefs. The private signM is involved in the updating process through Bayes＇ rule, and the neighbors＇ beliefs are embodied in through a weighted average form, where the weights are time-varying. The authors prove that agents eventually have correct forecasts for upcoming signals, and all the beliefs of agents reach a consensus. In addition, if there exists no state that is observationally equivalent to the true state from the point of view of all agents, the authors show that the consensus belief of the whole group eventually reflects the true state.

关键词： Consensus social learning social networks time-varying weights.

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Strip width spread prediction in rough rolling process based on mechanism modeling and optimization

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Journal of Iron and Steel Research International 2023年第12期30卷 2416-2424页

作者： Yan-jiu Zhong Jing-cheng Wang Jia-hui Xu Jun Rao Department of Automation Key Laboratory of System Control and Information ProcessingShanghai Jiao Tong UniversityShanghai 200240China

Aiming at the problems of low accuracy and poor robustness that existed in the current hot rolling strip width spread model,an improved strip spread prediction model based on a material forming mechanism and Bayesian optimized adaptive differential evolution algorithm(BADE)was *** first,we improved the original spread mechanism model by adding the weight and bias term to enhance the model robustness based on rolling ***,the BADE algorithm was proposed to optimize the improved spread mechanism *** optimization algorithm is based on a novel adaptive differential evolution algorithm,which can effectively achieve the global optimal ***,the prediction performances of five machine learning algorithms were compared in *** results show that the prediction accuracy of the improved spread model is obviously better than that of the machine learning algorithms,which proves the effectiveness of the proposed method.

关键词： Hot rolling Width spread prediction Bayesian optimization:Adaptive differential evolution Parameter optimization

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On the structural controllability of distributed systems with local structure changes

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Science China(information Sciences) 2018年第5期61卷 226-238页

作者： Jianbin MU Shaoyuan LI Jing WU Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of Automation Shanghai Jiao Tong University

This paper analyzes the structural controllability of distributed systems, which are composed of many subsystems and have complicated interconnections. Different from traditional methods in centralized systems where global information is required, the method proposed in this paper is based on local structural properties and simplified interconnections, by which the computational burden is highly decreased and the implementation is tractable. Moreover, a necessary condition for global structural controllability is obtained by combining local information. When the structure in any subsystems is changed, only corresponding local information needs to be re-evaluated instead of whole distributed systems, which makes the analysis ***, examples are given to illustrate the effectiveness of our proposed method.

关键词： structural controllability distributed systems subsystems structure changes graph theory

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Consensus protocol for heterogeneous multi-agent systems: A Markov chain approach

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Chinese Physics B 2013年第1期22卷 569-573页

作者：朱善迎陈彩莲关新平 Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education

This paper deals with the consensus problem for heterogeneous multi-agent systems. Different from most existing consensus protocols, we consider the consensus seeking of two types of agents, namely, active agents and passive agents. The objective is to directly control the active agents such that the states of all the agents would achieve consensus. In order to obtain a computational approach, we subtly introduce an appropriate Markov chain to cast the heterogeneous systems into a unified framework. Such a framework is helpful for tackling the constraints from passive agents. Furthermore, a sufficient and necessary condition is established to guarantee the consensus in heterogeneous multi-agent systems. Finally, simulation results are provided to verify the theoretical analysis and the effectiveness of the proposed protocol.

关键词： heterogeneous multi-agent system consensus protocol Markov chain

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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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Distributed Model Predictive control for Networked Plant-wide systems With Neighborhood Cooperation

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 108-117页

作者： Ting Bai Shaoyuan Li Yi Zheng the Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China IEEE

For large-scale networked plant-wide systems composed by physically(or geographically) divided subsystems, only limited information is available for local controllers on account of region and communication restrictions. Concerning the optimal control problem of such subsystems, a neighbor-based distributed model predictive control(NDMPC) strategy is presented to improve the global system performance. In this scheme, the performance index of local subsystems and that of its neighbors are minimized together in the determination of the optimal control input, which makes the local control decision also beneficial to its neighboring subsystems and further contributes to improving the convergence and control performance of overall *** stability of the closed-loop system is proved. Moreover, the parameter designing method for distributed synthesis is ***, the simulation results illustrate the main characteristics and effectiveness of the proposed control scheme.

关键词： Distributed control model predictive control (MPC) neighborhood cooperation plant-wide systems

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A fast network partition method for large-scale urban traffic networks

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控制理论与应用（英文版） 2013年第3期11卷 359-366页

作者： Zhao ZHOU Shu LIN Yugeng XI Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education

In order to control the large-scale urban traffic network through hierarchical or decentralized methods, it is necessary to exploit a network partition method, which should be both effective in extracting subnetworks and fast to compute. In this paper, a new approach to calculate the correlation degree, which determines the desire for interconnection between two adjacent intersections, is first proposed. It is used as a weight of a link in an urban traffic network, which considers both the physical characteristics and the dynamic traffic information of the link. Then, a fast network division approach by optimizing the modularity, which is a criterion to distinguish the quality of the partition results, is applied to identify the subnetworks for large-scale urban traffic networks. Finally, an application to a specified urban traffic network is investigated using the proposed algorithm. The results show that it is an effective and efficient method for partitioning urban traffic networks automatically in real world.

关键词： Traffic signal control Large-scale urban traffic networks Network partition

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification from Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital Department of Pathology Wuhan University Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20,000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Deducing Complete Selection Rule Set for Driver Nodes to Guarantee Network’s Structural controllability

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IEEE/CAA Journal of Automatica Sinica 2019年第5期6卷 1152-1165页

作者： Xichen Wang Yugeng Xi Wenzhen Huang Shuai Jia the Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai200240

Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.

关键词： Algebraic criteria complete selection rule set structural controllability driver nodes

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