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学者姓名：齐义文
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Abstract ：
Disturbances and uncertainties affect the performance of control systems and must be addressed. In addition, due to the potential privacy leakage caused by the informatization and networking of control systems, ensuring system privacy has become an important technical challenge. The topic of this paper is active disturbance rejection control (ADRC) with differential privacy preserving for switched multiple systems. By adding privacy noise with Laplace and uniform distribution to the system state, the novel privacy-preserving ADRC (PP-ADRC) framework ensures the required ADRC performance and privacy of system information in a non-ideal network environment. The innovation of this paper is embodied in three aspects: (i) The designed performance-dependent differential privacy preserving mechanism (PD-DPPM) under Laplace noise can adaptively balance system privacy and control performance. (ii) The presented privacy budget lower bound of uniform noise can determine the size of the uniform noise, making the PD-DPPM method more general in the field of privacy preservation. (iii) The newly constructed dual design of switching law and controller for PP-ADRC can ensure boundedness and H-infinity performance. Lastly, illustrative examples are provided to explain effectiveness. Note to Practitioners-In practical applications, active disturbance rejection control (ADRC), which consists of extended state observer (ESO), is a practical and effective technique for dealing with nonlinearity and uncertainty. In addition, for multimodal systems, the switched systems consisting of multiple subsystems and control laws can adjust the working mode for achieving better control performance according to changes in real-time system state. Therefore, ADRC is adopted to improve the control performance and efficiency of the switched systems. In the switched ADRC systems, the feedback channel carrying sensitive information about the system state and operation is a key link in closed-loop control. Once it is leaked or stolen, the operation and security of the control system will be destroyed. Therefore, designing a privacy-preserving method for switched ADRC systems to prevent sensitive feedback information from being stolen and ensure the safe and stable operation of the system is of great significance. The designed performance-dependent differential privacy preserving mechanism (PD-DPPM) can achieve privacy and security of feedback information based on real-time system performance, and achieve a balance between privacy and control.
Keyword ：
Active disturbance rejection control Active disturbance rejection control Automation Automation Control systems Control systems Differential privacy Differential privacy Noise Noise performance-dependent privacy preserving performance-dependent privacy preserving Privacy Privacy Protection Protection Real-time systems Real-time systems switched systems switched systems Switched systems Switched systems Switches Switches Uncertainty Uncertainty
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| GB/T 7714 | Qi, Yiwen , Wang, Chen , Zhang, Simeng et al. Performance-Dependent Privacy Preserving for Switched Multiple Systems Under Active Disturbance Rejection Control [J]. | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2025 , 22 : 17209-17220 . |
| MLA | Qi, Yiwen et al. "Performance-Dependent Privacy Preserving for Switched Multiple Systems Under Active Disturbance Rejection Control" . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 22 (2025) : 17209-17220 . |
| APA | Qi, Yiwen , Wang, Chen , Zhang, Simeng , Ahn, Choon Ki . Performance-Dependent Privacy Preserving for Switched Multiple Systems Under Active Disturbance Rejection Control . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2025 , 22 , 17209-17220 . |
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Accurate segmentation of lesions in lung CT images remains challenging due to blurred boundaries, small lesion sizes, and the scarcity of annotated data. To address these issues, this paper proposes a semi-supervised contrastive learning framework with a novel multiple attention UNet (MA-UNet) for lung CT image segmentation. The MA-UNet integrates a dual-attention module (DAM) and attention gates (AGs) to enhance spatial-channel feature refinement and boundary sensitivity. The DAM captures global context and channel-wise dependencies, while the AG emphasizes lesion-related features. Furthermore, residual blocks are used to improve gradient propagation and computational efficiency. To overcome limited annotations, we propose a contrastive learning framework that can fully utilize both labeled and unlabeled data to improve segmentation accuracy. To verify the validity of the methods and parameters design in this paper, we systematically carry out multiple ablation experiments. The experimental results show that the Dice, MIoU and Recall scores of MA-UNet based on comparative learning with only 1/2 ratio of labeled data are 78.41%, 88.78% and 91.79%, respectively, which are close to its supervised segmentation model, which effectively overcomes the problem of lack of labeled data.
Keyword ：
Attention mechanism Attention mechanism Contrastive learning Contrastive learning Lung CT image Lung CT image Semi-supervised segmentation Semi-supervised segmentation
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| GB/T 7714 | Qi, Yiwen , Yao, Caibin , Chen, Hao et al. Semi-supervised segmentation of lung CT images based on contrastive learning [J]. | SIGNAL IMAGE AND VIDEO PROCESSING , 2025 , 19 (7) . |
| MLA | Qi, Yiwen et al. "Semi-supervised segmentation of lung CT images based on contrastive learning" . | SIGNAL IMAGE AND VIDEO PROCESSING 19 . 7 (2025) . |
| APA | Qi, Yiwen , Yao, Caibin , Chen, Hao , Wang, Xufei . Semi-supervised segmentation of lung CT images based on contrastive learning . | SIGNAL IMAGE AND VIDEO PROCESSING , 2025 , 19 (7) . |
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Abstract ：
Differential privacy is an effective method to solve data privacy leakage. The common differential privacy method is achieved by adding privacy noises to the transmitted data, which may affect data accuracy. For the control system, data accuracy greatly affects the system performance. To circumvent this difficulty, we propose a novel privacy-preserved rolling optimization strategy (PP-ROS) for switched systems. The main contributions are reflected in three aspects: 1) The proposed PP-ROS is used to calculate the private control input by adding Laplace noise to the prediction and control horizons, instead of the transmitted data. 2) Privacy definitions of the prediction and control horizons are presented, and a private model predictive control (P-MPC) controller design is provided based on the PP-ROS. The P-MPC controller achieves the privacy of its parameters. 3) Under PP-ROS and P-MPC, the proof and calculation methods for the privacy levels of control input and system output are given. The results indicate that when noise is added to the horizons, both control input and system output are private. Finally, the availability and benefits of PP-ROS and P-MPC are demonstrated using two simulation examples and comparison results.
Keyword ：
Accuracy Accuracy Control horizon Control horizon differential privacy differential privacy Differential privacy Differential privacy Heuristic algorithms Heuristic algorithms model predictive control (MPC) model predictive control (MPC) Noise Noise Optimal control Optimal control prediction horizon prediction horizon Predictive control Predictive control Privacy Privacy Stability analysis Stability analysis switched systems switched systems Switched systems Switched systems System performance System performance
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| GB/T 7714 | Qi, Yiwen , Guo, Shitong , Ahn, Choon Ki et al. Privacy for Switched Systems Under MPC: A Privacy-Preserved Rolling Optimization Strategy [J]. | IEEE TRANSACTIONS ON CYBERNETICS , 2025 , 55 (5) : 2085-2097 . |
| MLA | Qi, Yiwen et al. "Privacy for Switched Systems Under MPC: A Privacy-Preserved Rolling Optimization Strategy" . | IEEE TRANSACTIONS ON CYBERNETICS 55 . 5 (2025) : 2085-2097 . |
| APA | Qi, Yiwen , Guo, Shitong , Ahn, Choon Ki , Tang, Yiwen , Huang, Jie . Privacy for Switched Systems Under MPC: A Privacy-Preserved Rolling Optimization Strategy . | IEEE TRANSACTIONS ON CYBERNETICS , 2025 , 55 (5) , 2085-2097 . |
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This paper explores online learning model predictive control (MPC) for switched systems with stable terminal constraints. In order to reduce the computational burden, we decompose the infinite horizon MPC into n finite horizons, and adopt adaptive dynamic programming (ADP) to assist MPC in online solving the optimal control problem in each finite horizon. Further, we use a set of stable terminal constraints to ensure both the convergence of online learning MPC in each finite horizon and the connection of adjacent finite horizons. In addition, in order to ensure the uniform ultimate boundedness (UUB) of the triggered switched systems, on the one hand, a novel performance dependent mixed switching law (PD-MSL) is proposed to both avoid frequent switching and take advantage of performance dependent decision-making; on the other hand, an analytical framework of the coupling between mode switching and event-triggering is proposed. Finally, the validity of the presented approach is demonstrated through simulations.
Keyword ：
Online learning MPC Online learning MPC Performance dependent mixed switching law Performance dependent mixed switching law Stable terminal constraints Stable terminal constraints Switched systems Switched systems
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| GB/T 7714 | Qi, Yiwen , Lv, Yanbo , Qu, Ziyu et al. Online learning MPC for switched systems with performance dependent mixed switching law [J]. | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS , 2024 , 361 (15) . |
| MLA | Qi, Yiwen et al. "Online learning MPC for switched systems with performance dependent mixed switching law" . | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 361 . 15 (2024) . |
| APA | Qi, Yiwen , Lv, Yanbo , Qu, Ziyu , Guo, Shitong . Online learning MPC for switched systems with performance dependent mixed switching law . | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS , 2024 , 361 (15) . |
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This paper explores event-triggered model predictive control (MPC) for constrained switched systems, incorporating a buffer-based anti-attack (BBAA) approach to ensure network security. Since the system state is unknown and disturbed, an observer-based $ H_{\infty } $ H infinity MPC approach is used to estimate the system state and suppress disturbance. Furthermore, the estimated state and control input can be optimised by minimising the performance function. Considering that the system state is subject to denial of service (DoS) attacks in the feedback channel, the BBAA approach is used to reconstruct the estimated state, thereby reducing the impact of attacks on system performance. To improve the utilisation of network resources, a set of event-triggering mechanisms (ETMs) is used. In addition, a set of matrix inequality conditions is given to constrain the gains of controllers and observers. Then, the system $ H_{\infty } $ H infinity performance is demonstrated by applying the average dwell time (ADT) and the Lyapunov function method, and the complex coupling between model switching, DoS attacks and event-triggering is analysed. Simulation results validate the effectiveness of the proposed approach.
Keyword ：
buffer-based anti-attack approach buffer-based anti-attack approach DoS attacks DoS attacks model predictive control model predictive control Switched systems Switched systems
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| GB/T 7714 | Lv, Yanbo , Qi, Yiwen , Guo, Shitong et al. Enhancing network security in constrained switched systems: event-triggered MPC with a buffer-based anti-attack approach [J]. | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2024 , 55 (14) : 2963-2979 . |
| MLA | Lv, Yanbo et al. "Enhancing network security in constrained switched systems: event-triggered MPC with a buffer-based anti-attack approach" . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 55 . 14 (2024) : 2963-2979 . |
| APA | Lv, Yanbo , Qi, Yiwen , Guo, Shitong , Qu, Ziyu , Li, He . Enhancing network security in constrained switched systems: event-triggered MPC with a buffer-based anti-attack approach . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2024 , 55 (14) , 2963-2979 . |
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This brief studies a new resilient event-triggered model-free adaptive predictive control (MFAPC) method with anti-attacks for disturbed switched nonlinear systems in non-ideal network. The switched nonlinear systems are transformed into equivalent dynamic data models by dynamic linearization. Considering the denial of service (DoS) attacks in non-ideal network environment, an anti-attacks method based on a hold mechanism and a resilient event-triggering strategy (RETS) is considered, which reduces attacks impact on system performance. A parameter estimator is given to estimate the external disturbance and further obtain accurate system models. In addition, a new tracking error boundedness analysis method is given by using the average dwell time (ADT) technique and Lyapunov function. Finally, motor simulation results are given to verify the applicability of the proposed method.
Keyword ：
Adaptation models Adaptation models Data models Data models DoS attacks DoS attacks Integrated circuit modeling Integrated circuit modeling MFAPC MFAPC Nonlinear systems Nonlinear systems Predictive models Predictive models RETS RETS Switched nonlinear systems Switched nonlinear systems Switched systems Switched systems Switches Switches tracking error tracking error
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| GB/T 7714 | Qi, Yiwen , Guo, Shitong , Tang, Yiwen . Optimal Output Tracking for Switched Systems Under DoS Attacks: A Model-Free Adaptive Predictive Control Method [J]. | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS , 2024 , 71 (1) : 266-270 . |
| MLA | Qi, Yiwen et al. "Optimal Output Tracking for Switched Systems Under DoS Attacks: A Model-Free Adaptive Predictive Control Method" . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 71 . 1 (2024) : 266-270 . |
| APA | Qi, Yiwen , Guo, Shitong , Tang, Yiwen . Optimal Output Tracking for Switched Systems Under DoS Attacks: A Model-Free Adaptive Predictive Control Method . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS , 2024 , 71 (1) , 266-270 . |
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This article studies learning empirical inherited intelligent model predictive control (LEII-MPC) for switched systems. For complex environments and systems, an intelligent control method design with learning ability is necessary and meaningful. First, a switching law that coordinates the iterative learning control action is devised according to the average dwell time approach. Second, an intelligent MPC mechanism with the iteration learning experience is designed to optimize the control action. With the designed LEII-MPC, sufficient conditions for the switched systems stability equipped with the event-triggering schemes (ETSs) in both the time domain and the iterative domain are presented. The ETS in the iterative domain is to solve unnecessary iterative updates. The ETS in the time domain is to deal with potential denial of service (DoS) attacks, which includes two parts: 1) for detection, an attack-dependent event-triggering method is presented to determine attack sequence and reduce lost packets; and 2) for compensation, a buffer is used to ensure system performance during the attack period. Last, a numerical example shows the effectiveness of the proposed method. © 2020 IEEE.
Keyword ：
Predictive control systems Predictive control systems Self-supervised learning Self-supervised learning
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| GB/T 7714 | Qi, Yiwen , Tang, Yiwen , Yu, Wenke . Learning Empirical Inherited Intelligent MPC for Switched Systems With Network Security Communication [J]. | IEEE Transactions on Artificial Intelligence , 2024 , 5 (12) : 6342-6355 . |
| MLA | Qi, Yiwen et al. "Learning Empirical Inherited Intelligent MPC for Switched Systems With Network Security Communication" . | IEEE Transactions on Artificial Intelligence 5 . 12 (2024) : 6342-6355 . |
| APA | Qi, Yiwen , Tang, Yiwen , Yu, Wenke . Learning Empirical Inherited Intelligent MPC for Switched Systems With Network Security Communication . | IEEE Transactions on Artificial Intelligence , 2024 , 5 (12) , 6342-6355 . |
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In this paper, the robust security protection control for switched systems is studied. A robust antidisturbance mechanism using the Radial Basis Function Neural Network (RBFNN) is proposed for switched systems, which can approximate and compensate for the impact of unknown disturbance on the system state. Then, a network security protection mechanism based on encoder and decoder is presented, which has the ability to resist the dual impact on the feedback information caused by the network privacy snooping and data injection attacks. Accordingly, stability analysis and state -feedback controller design are given for the switched systems under unknown disturbance, network privacy snooping and injection attacks. Finally, simulation results illustrate the effectiveness of the proposed method.
Keyword ：
Injection attacks Injection attacks Network security protection Network security protection Privacy snooping Privacy snooping Robust anti-disturbance Robust anti-disturbance Switched systems Switched systems
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| GB/T 7714 | Wang, Chen , Qi, Yiwen , Tang, Yiwen et al. Robust control with protected feedback information for switched systems under injection attacks [J]. | APPLIED MATHEMATICS AND COMPUTATION , 2024 , 475 . |
| MLA | Wang, Chen et al. "Robust control with protected feedback information for switched systems under injection attacks" . | APPLIED MATHEMATICS AND COMPUTATION 475 (2024) . |
| APA | Wang, Chen , Qi, Yiwen , Tang, Yiwen , Li, Xin , Ji, Ming . Robust control with protected feedback information for switched systems under injection attacks . | APPLIED MATHEMATICS AND COMPUTATION , 2024 , 475 . |
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This paper proposes an optimal output synchronization control method for heterogeneous multi -agent systems (HMASs) under a performance -dependent switching topology and DoS attacks. First, local and global switched performance index functions (SPIF) and SPIF-dependent topology switching law are proposed, respectively, thus, the control performance and topology quality can be quantitatively expressed. Second, an adaptive dynamic programming (ADP) algorithm with mode switching is proposed, aimed at dealing with the difficult Hamilton-Jacobi- Bellman equation, as well as the analytical complexity caused by the switching dynamics. The convergence of the switched ADP algorithm is proven to ensure its correct implementation. Then, for different topologies, multi -mode Actor-Critic neural networks (NNs) are built for each agent to calculate optimized control policies and SPIF, respectively. Furthermore, an NNbased state compensation mechanism is designed to expand the applicability of the designed switched ADP algorithm when the leader's output transmission is unreliable. Finally, the results of numerical examples confirm that the proposed method is feasible.
Keyword ：
DoS attacks DoS attacks Heterogeneous multi-agent systems Heterogeneous multi-agent systems Switched adaptive dynamic programming Switched adaptive dynamic programming Switching topology Switching topology
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| GB/T 7714 | Qi, Yiwen , Wang, Yunlong , Geng, Honglin et al. Optimal synchronization for multi-agent systems: A performance-dependent switching topology [J]. | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS , 2024 , 361 (6) . |
| MLA | Qi, Yiwen et al. "Optimal synchronization for multi-agent systems: A performance-dependent switching topology" . | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 361 . 6 (2024) . |
| APA | Qi, Yiwen , Wang, Yunlong , Geng, Honglin , Xing, Ning , Zheng, Zonghua , Li, He . Optimal synchronization for multi-agent systems: A performance-dependent switching topology . | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS , 2024 , 361 (6) . |
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In this article, the full differential privacy-preserving problem for switched LPV systems is concerned. The security of a control system is the ability to avoid intentional sabotage or accidental interference affecting its normal operation. For switched LPV systems, it contains both internal (scheduling variable and switching signal) and external (system output) information that needs to be protected, we adopt differential privacy to achieve its full privacy preserving. The resulting challenges are: 1) privacy design for three types of system signals and 2) dual asynchronization analysis under triple privacy noise. Accordingly, three differential privacy definitions and Laplace (resp. uniform) noise design methods are presented. Sufficient conditions for H-infinity control design with dual asynchronization analysis are given. Finally, simulation results verify the effectiveness of the proposed method.
Keyword ：
Databases Databases Data privacy Data privacy Differential privacy Differential privacy Dual asynchronization Dual asynchronization Dynamical systems Dynamical systems full differential privacy preserving full differential privacy preserving H-infinity control H-infinity control Privacy Privacy Security Security switched LPV systems switched LPV systems Switches Switches
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| GB/T 7714 | Qi, Yiwen , Tang, Yiwen , Kawano, Yu . Full Differential Privacy Preserving for Switched LPV Systems [J]. | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS , 2024 , 54 (5) : 3153-3163 . |
| MLA | Qi, Yiwen et al. "Full Differential Privacy Preserving for Switched LPV Systems" . | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 54 . 5 (2024) : 3153-3163 . |
| APA | Qi, Yiwen , Tang, Yiwen , Kawano, Yu . Full Differential Privacy Preserving for Switched LPV Systems . | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS , 2024 , 54 (5) , 3153-3163 . |
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