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An enhanced equivalent input disturbance approach to current control of PMSM with periodic and aperiodic disturbances

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Science China(information Sciences) 2025年第3期68卷 272-285页

作者： Tao YANG Youwu DU Bo LI Weihua CAO Chuanke ZHANG Jinhua SHE School of Electrical & Information Jiangsu University of Technology School of Automation China University of Geosciences School of Engineering Tokyo University of Technology

The current-loop control of a permanent magnet synchronous motor(PMSM) system suffers from periodic and aperiodic disturbances, which result in current ripples and degrade control performance. This paper presents an enhanced equivalent-input-disturbance(EID) approach to reject periodic and aperiodic disturbances in the current loop of a *** additional quasi-resonant compensators(QRCs) are integrated into a conventional EID estimator with a low-pass filter(LPF) to handle the disturbances. The configuration of an enhanced EID(EEID)-based control system for PMSM current loop is explained. An analysis in the frequency domain shows the mechanism of the presented method for rejecting periodic and aperiodic disturbances simultaneously. It reveals that the sensitivity reduction of the system for aperiodic disturbances is mainly determined by the bandwidth of the LPF and that for periodic disturbances is determined by the parameters of the *** stability of the system is analyzed using the Nyquist stability criterion. The design algorithm for system parameters is provided. Compared to the conventional EID approach, the proposed method provides an additional degree of freedom to deal with periodic disturbances. The design of the QRCs is independent of each other, which makes the proposed method flexible and easy to implement. The effectiveness and the superiority of the EEID approach are validated by simulation results of a PMSM system.

关键词： equivalent input disturbance (EID) disturbance rejection permanent magnet synchronous motor (PMSM) periodic and aperiodic disturbances quasi-resonant compensator

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Dynamic event-triggered data-driven iterative learning bipartite tracking control for nonlinear MASs with prescribed performance

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Science China(information Sciences) 2025年第1期68卷 292-305页

作者： Tao SHI Wei-Wei CHE School of Mechatronic Engineering and Automation Shanghai University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University College of Information Science and Engineering Northeastern University

This article proposes a distributed dynamic event-triggered data-driven iterative learning control(DET-DDILC)scheme under a predefined performance to tackle the bipartite tracking control problem for multiagent systems(MASs). An improved dynamic linearization technique is utilized to convert the nonlinear MASs into an iterative linear data model. First,a peer-to-peer mapping function is introduced to map the constrained distributed system output homeomorphism to an unconstrained one. In addition, a DET mechanism based on a time-iteration-varying function is devised to conserve network communication resources. Based on the unconstrained transformation and the designed DET mechanism, the DET-DDILC algorithm is devised to ensure that the bipartite tracking performance of MASs can be within the preset range. Finally, the effectiveness and feasibility of the designed control scheme are demonstrated via a simulation case by a comparison.

关键词： bipartite tracking control prescribed performance event-triggered iterative learning control multiagent systems

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New results on finite-time stability and instability theorems for stochastic nonlinear time-varying systems

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Science China(information Sciences) 2025年第2期68卷 186-199页

作者： Weihai ZHANG Liqiang YAO College of Electrical Engineering and Automation Shandong University of Science and Technology School of Mathematics and Information Science Yantai University

This paper studies finite-time stability and instability theorems in the probability sense for stochastic nonlinear timevarying systems. Firstly, a new sufficient condition is proposed to guarantee that the considered system has a global ***, we propose new finite-time stability and instability criteria that relax the constraints on LV(the infinitesimal operator of Lyapunov function V) by the uniformly asymptotically stable function. On the one hand, these obtained results make up for the shortcomings of the existing results. On the other hand, the new finite-time stability theorems can be viewed as natural extensions of the existing results and also allow LV to be indefinite(negative or positive) rather than just only allow LV < ***, some simulation examples verify the validity of the theoretical results.

关键词： stochastic nonlinear systems finite-time stability finite-timeinstability uniformly asymptotically stable function

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K-Corruption Intermittent Attacks for Violating the Codiagnosability

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 159-172页

作者： Ruotian Liu Yihui Hu Agostino Marcello Mangini Maria Pia Fanti IEEE the Department of Electrical and Information Engineering Polytechnic University of Bari the School of Automation Xi'an University of Posts and Telecommunications

In this work, we address the codiagnosability analysis problem of a networked discrete event system under malicious attacks. The considered system is modeled by a labeled Petri net and is monitored by a series of sites, in which each site possesses its own set of sensors, without requiring communication among sites or to any coordinators. A net is said to be codiagnosable with respect to a fault if at least one site could deduce the occurrence of this fault within finite steps. In this context, we focus on a type of malicious attack that is called stealthy intermittent replacement attack. The stealthiness demands that the corrupted observations should be consistent with the system's normal behavior, while the intermittent replacement setting entails that the replaced transition labels must be recovered within a bounded of consecutive corrupted observations(called as K-corruption intermittent attack). Particularly, there exists a coordination between attackers that are separately effected on different sites, which holds the same corrupted observation for each common transition under attacks. From an attacker viewpoint, this work aims to design Kcorruption intermittent attacks for violating the codiagnosability of systems. For this purpose, we propose an attack automaton to analyze K-corruption intermittent attack for each site, and build a new structure called complete attack graph that is used to analyze all the potential attacked paths. Finally, an algorithm is inferred to obtain the K-corruption intermittent attacks, and examples are given to show the proposed attack strategy.

关键词： Codiagnosability decentralized structure discrete event system intermittent attack Petri net

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Encoded Marker Clusters for Auto-Labeling in Optical Motion Capture

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ACM Transactions on Graphics 2025年第2期44卷 1-16页

作者： Wang, Hao Hou, Taogang Liu, Tianhui Li, Jiaxin Wang, Tianmiao School of Automation and Intelligence Beijing Jiaotong University Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

Marker-based optical motion capture (MoCap) is a vital tool in applications such as virtual production, and movement sciences. However, reconstructing scattered MoCap data into real motion sequences is challenging, and data processing is time-consuming and labor-intensive. Here we propose a novel framework for MoCap auto-labeling and matching. In this framework, we designed novel clusters of reflective markers called auto-labeling encoded marker clusters (AEMCs), including clusters with an explicit header (AEMCs-E) and an implicit header (AEMCs-I). Combining cluster design and coding theory gives each cluster a unique codeword for MoCap auto-labeling and matching. Moreover, we provide a method of mapping and decoding for cluster labeling. The labeling results are only determined by the intrinsic characteristics of the clusters instead of the skeleton structure or posture of the subjects. Compared with commercial software and data-driven methods, our method has better labeling accuracy in heterogeneous targets and unknown marker layouts, which demonstrates the promising application of motion capture in humans, rigid or flexible robots. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data reduction

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Cooperative output regulation of heterogeneous directed multi-agent systems:a fully distributed model-free reinforcement learning framework

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Science China(information Sciences) 2025年第2期68卷 170-185页

作者： Xiongtao SHI Yanjie LI Chenglong DU Huiping LI Chaoyang CHEN Weihua GUI Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and AutomationHarbin Institute of Technology (Shenzhen) School of Automation Central South University School of Marine Science and Technology Northwestern Polytechnical University School of Information and Electrical Engineering Hunan University of Science and Technology

In this paper, the cooperative output regulation(COR) problem of a class of unknown heterogeneous multi-agent systems(MASs) with directed graphs is studied via a model-free reinforcement learning(RL) based fully distributed eventtriggered control(ETC) strategy. First, we consider the scenario that the exosystem is accessible globally to all agents, an internal model-based augmented algebraic Riccati equation(AARE) is constructed, and its solution is learned by the proposed model-free RL algorithm via online input-output data. Further, for the scenario that the exosystem is accessible only to its adjacent followers, the distributed observers are designed for each agent to get the state of the exosystem, and an internal modelbased fully distributed adaptive ETC protocol is then synthesized to construct the corresponding AARE, and the feedback gain matrix is learned in a model-free fashion. The model-free RL-based control protocol proposed in this paper can not only remove the prior knowledge of agents' dynamics, but also release the dependence on global information by the adaptive event-triggered mechanism(ETM) and the new graph-based Lyapunov function. Finally, simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.

关键词： model-free reinforcement learning unknown heterogeneous multi-agent systems fully distributed event-triggered control directed graph

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Controllability of heterogeneous networked sampled-data systems

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Science China(information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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A Parallel Dual-Branch Deep Learning Framework Integrating VMD Feature engineering and Multiscale Temporal Feature Fusion for Small-Sample Fault Diagnosis

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IEEE Sensors Journal 2025年第7期25卷 12479-12495页

作者： Haixiao, Cao Chuanlong, Ding Jiang, Jiang Yonghong, Zhang Qi, Liu Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210044 China Wuxi University School of Automation Wuxi214105 China

Rolling bearings are crucial in mechanical systems, where failures pose safety risks and economic losses. However, their rarity makes timely fault detection and data collection challenging. To address this, a parallel dual-branch fault diagnosis model was proposed. One branch applied variational mode decomposition (VMD) with the hybrid particle swarm optimization (HPSO) algorithm to automatically and optimally decompose the raw signals. Then, continuous wavelet transform (CWT) was used on the decomposed modes to create stacked feature maps, which was followed by the normalization with a engineering × engineering convolution to accomplish the feature engineering. Next, the improved convolutional neural networks (CNNs) and the bidirectional long short-term memory (BiLSTM) models were used in sequence to extract features from both the frequency and temporal domains. In the other branch, the original signal was downsampled at three different step sizes to capture multiscale temporal representations, and the multilayer perceptrons (MLPs) were employed to learn temporal features from different time scales, which were fused into one feature output thereafter. Eventually, the time-frequency and the temporal features from both branches were concatenated and passed to the output for fault diagnosis. The proposed feature engineering method and the parallel dual-branch fault diagnosis model were evaluated on small datasets containing 20 samples from Case Western Reserve University (CWRU), achieving an impressive 100% accuracy. Moreover, the model was compared with recent mainstream models on the Paderborn (PU) dataset. The results demonstrated that it excelled at learning key features from small samples, highlighting its potential for small-sample rolling bearing fault diagnosis. © 2025 IEEE.

关键词： Convolution

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Asymptotical event-based input-output constrained boundary control of flexible manipulator agents under a signed digraph

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Science China(information Sciences) 2025年第4期68卷 319-335页

作者： Xiangqian YAO Xiangmin XU Wei HE Yu LIU School of Future Technology South China University of Technology School of Automation and Institute of Artificial Intelligence Beijing Information Science and Technology University School of Intelligence Science and Technology University of Science and Technology Beijing School of Automation Science and Engineering South China University of Technology

This article tackles the boundary event-based bipartite consensus tracking control problem for the flexible manipulator multi-agent network over a signed diagraph. Each follower agent is the flexible manipulator with unknown disturbances,modeling uncertainties, input saturations and backlashes, and asymmetric output constraints. To reduce the continuous updating of control inputs, a new dynamic event-triggering mechanism is used. Under multiple constraints, achieving the asymptotic convergence point by point in space of the manipulator's vibration state is a control challenge. To solve this issue, we propose a new asymptotic convergence lemma. In control design, radial basis neural networks are employed to estimate nonlinear uncertain terms and the barrier Lyapunov function is used to accomplish the output constraints. Based on the Lyapunov direct method, a novel distributed boundary event-based control algorithm is designed to guarantee that the closed-loop network can reach the asymptotical bipartite consensus tracking and vibration suppression. Moreover, Zeno behaviors can be excluded for each agent. Finally, some numerical results are presented to demonstrate the validity and superiority of the designed control algorithm.

关键词： flexible-link manipulator input-output constraint event-based asymptotical bipartite tracking vibrationprotectłinebreak control

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Identification algorithm of low-count energy spectra under short-duration measurement based on heterogeneous sample transfer

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Nuclear Science and Techniques 2025年第3期36卷 12-26页

作者： Hao-Lin Liu Hai-Bo Ji Jiang-Mei Zhang Jing Lu School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China Department of Automation University of Science and Technology of ChinaHefei 230026China Fundamental Science on Nuclear Wastes and Environment Safety Laboratory Southwest University of Science and TechnologyMianyang 621010China School of Automation and Information Engineering Sichuan University of Science and EngineeringZigong 643000China

In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical *** issues can lead to potential failures in peak-searching-based identification *** address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification *** experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma *** only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain *** proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.

关键词： Radionuclide identification Low-count Gamma energy spectral analysis Heterogeneous Transfer learning

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