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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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A generalized rough set-based information flling technique for failure analysis of thruster experimental data

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Chinese Journal of Aeronautics 2013年第5期26卷 1182-1194页

作者： Han Shan Zhu Qiang Li Jianxun Chen Lin Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

Interval-valued data and incomplete data are two key problems for failure analysis of thruster experimental data and have been basically solved by the proposed methods in this paper. Firstly, information data acquired from the simulation and evaluation system formed as intervalvalued information system （IIS） is classified by the interval similarity relation. Then, as an improvement of the classical rough set, a new kind of generalized information entropy called ＂H＇-information entropy＂ is suggested for the measurement of uncertainty and the classification ability of IIS. There is an innovative information filling technique using the properties of H＇-information entropy to replace missing data by some smaller estimation intervals. Finally, an improved method of failure analysis synthesized by the above achievements is presented to classify the thruster experimental data, complete the information, and extract the failure rules. The feasibility and advantage of this method is testified by an actual application of failure analysis, whose performance is evaluated by the quantification of E-condition entropy.

关键词： Data acquisition Data classification Failure analysis information filling Rough set

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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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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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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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Event-Triggered Distributed Multitarget Tracking With Unknown Clutter Rate and Detection Profile

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zheng, Litao Yang, Feng Shi, Lihong Guo, Zhengyu Cai, Yunze Shanghai Jiao Tong University Department of Automation Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Northwestern Polytechnical University School of Automation Xi'an 710129 China Key Lab of Information Fusion Technology Ministry of Education of China Xi'an 710129 China National Key Laboratary of Air-based Information Perceptian and Fusion Luoyang China State Key Laboratory of Submarine Geoscience Shanghai 201913 China

This paper addresses communication bandwidth reduction and energy efficiency enhancement of a peer-to-peer sensor network for distributed multitarget tracking under unknown clutter rate and detection profile. We propose an event-triggered distributed bootstrap cardinalized probability hypothesis density (CPHD) filter, where the local filter consists of an estimator that estimates the clutter and detection parameters, and a tracker that estimates the number and states of targets. Specifically, the proposed approach enforces each sensor to broadcast its local posterior density only when it has high estimation quality and significant information gain, wherein the former is determined by the outputs of the local estimator and tracker, while the latter is measured via the Jensen-Shannondivergence. Then, we develop a modified weighted arithmetic average fusion method to separately fuse the cardinality distributions and intensity functions, in which the fusion weights are constructed based on estimation qualities and triggering thresholds, which is incorporated into the distributed flooding scheme for distributed averaging. Additionally, the Gaussian mixture implementations of the proposed event-triggered distributed bootstrap CPHD filter are given, where only Gaussian components with high weights are applied, thus reducing the effect of false alarms and, consequently, achieving a partial consensus across the network. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments. © 1965-2011 IEEE.

关键词： arithmetic average bootstrap filter distributed flooding Distributed multitarget tracking event-triggered

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Prescribed Performance control for a Nonlinear system With Actuator Saturation via Anti-Windup Design

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IEEE Transactions on Circuits and systems I: Regular Papers 2025年

作者： Lai, Wenxin Li, Yuanlong Lin, Zongli Shanghai Jiao Tong University Department of Automation Shanghai 200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China University of Virginia Charles L. Brown Department of Electrical and Computer Engineering Charlottesville 22904 VA United States

In this paper, within the prescribed performance control framework, we revisit the output tracking problem of a nonlinear system with input saturation, user-specified performance and external disturbances. To handle the intrinsic conflict between actuator saturation and performance requirements, we introduce a novel auxiliary system, which is driven by an artificial saturation nonlinearity, to generate modification signals for relaxing the prescribed performance functions. To further alleviate the adverse effects caused by actuator saturation, we incorporate a new performance-based anti-windup compensator into the control framework. In particular, the auxiliary system is designed to adjust the external performance requirements, and the anti-windup compensator is used for improving the internal saturation handling capability. Moreover, we employ a predetermined weighting coefficient to balance between the auxiliary system and the anti-windup compensator for better control performance. To deal with external disturbances, we construct a series of disturbance observers. With the help of dynamic surface control strategies, we develop a state-feedback control law. Theoretical analysis establishes the boundedness of all signals. Finally, an academic example and a tunnel diode circuit system are provided to demonstrate the effectiveness of our control strategy. © 2004-2012 IEEE.

关键词： activation mechanism Actuator saturation anti-windup disturbance observers prescribed performance reference tracking

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A Full-Lifecycle Calibration Method for Camera and LiDAR in Autonomous Driving

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Wei, Ming Lu, Jun-Guo Ye, Nan Zhu, Zhen Zhang, Qinghao Wang, Yafei Shanghai Jiao Tong University Ministry of Education of China Department of Automation and the Key Laboratory of System Control and Information Processing Shanghai200240 China Nanjing University of Aeronautics and Astronautics College of Mechanical and Electrical Engineering Nanjing210016 China Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200240 China

In recent years, advancements in light laser detection and ranging (LiDAR) and camera technologies have brought increasing attention to autonomous driving. Sensor fusion provides complementary information that overcomes the limitations of individual sensors and improves the safety of autonomous vehicles. The key to achieving this fusion lies in sensor calibration. This article presents a full-lifecycle calibration method that integrates offline and online processes to achieve high-precision and efficient calibration for camera-LiDAR systems in autonomous driving. The proposed approach unifies the calibration stages, addressing both the initial factory calibration and the dynamic adjustments required during vehicle operation. Offline calibration is performed using specialized calibration boards and standardized workflows to establish accurate initial parameters, ensuring a robust foundation for subsequent operations. Online calibration leverages a learning-based, end-to-end deep declarative network to dynamically adjust calibration parameters in real time, compensating for sensor displacement caused by vibration, loosening, or collisions. Extensive experiments are conducted to validate the proposed method. The accuracy and robustness of the offline calibration are validated through quantitative and qualitative results in simulated and real-world tests. Competitive precision in online calibration is demonstrated on public datasets, with average translation errors of 0.667 and 1.937 cm, and average rotation errors of 0.149° and 0.138° achieved on the KITTI and NuScenes datasets, respectively. Additionally, the online calibration method’s real-time capability is confirmed in practical experiments, with a frame rate of approximately 11 frames/s. This full-lifecycle calibration method significantly improves the accuracy, reliability, and long-term stability of autonomous driving systems, addressing critical challenges in sensor calibration across diverse environments. © 1

关键词： Autonomous vehicles

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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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