基于混沌数据加密的切换系统最优控制与隐私保护

齐义文; 乔鑫鑫; 邓飞其; 王云龙

doi:10.16383/j.aas.c250636

基于混沌数据加密的切换系统最优控制与隐私保护

doi: 10.16383/j.aas.c250636 cstr: 32138.14.j.aas.c250636

1.
福州大学电气工程与自动化学院福州 350108
2.
华南理工大学自动化科学与工程学院广州 510640
3.
沈阳航空航天大学自动化学院沈阳 110135

基金项目: 国家自然科学基金(62373110)资助

详细信息

作者简介:
齐义文：福州大学电气工程与自动化学院教授. 2012年获得哈尔滨工业大学博士学位. 主要研究方向为切换系统, 隐私保护, 学习控制. E-mail: qiyiwen@fzu.edu.cn

乔鑫鑫：福州大学电气工程与自动化学院硕士研究生. 主要研究方向为隐私保护, 安全约束, 自适应动态规划. E-mail: qiaoxinxin107@163.com

邓飞其：华南理工大学自动化科学与工程学院教授. 1997年获得华南理工大学博士学位. 主要研究方向为智能控制系统, 系统工程. 本文通信作者. E-mail: aufqdeng@scut.edu.cn

王云龙：沈阳航空航天大学自动化学院硕士研究生. 主要研究方向为切换系统, 隐私保护, 自适应动态规划. E-mail: yunlong_sau@126.com

计量
- 文章访问数: 12
- HTML全文浏览量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2025-11-14
- 录用日期: 2026-01-30
- 网络出版日期: 2026-03-27

Optimal Control and Privacy Preserving of Switched Systems Based on Chaotic Data Encryption

1.
College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108
2.
School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640
3.
School of Automation, Shenyang Aerospace University, Shenyang 110135

Funds: Supported by National Natural Science Foundation of China(62373110)

More Information

Author Bio:
QI Yi-Wen　Professor at the College of Electrical Engineering and Automation, Fuzhou University. He received his Ph.D. degree from Harbin Institute of Technology in 2012. His research interests include switched systems, privacy preserving, and learning control

QIAO Xin-Xin　Master student at the College of Electrical Engineering and Automation, Fuzhou University. His research interests include privacy preserving, security constraint, and adaptive dynamic programming

DENG Fei-Qi　Professor at the School of Automation Science and Engineering, South China University of Technology. He received his Ph.D. degree from South China University of Technology in 1997. His research interests include intelligent control system and system engineering. Corresponding author of this paper

WANG Yun-Long　Master student at the School of Automation, Shenyang Aerospace University. His research interests include switched systems, privacy preserving, and adaptive dynamic programming

摘要

摘要: 针对控制系统中数据经网络传输存在的隐私泄露以及隐私保护导致的性能损失问题, 本文研究一种具有隐私保护的切换系统最优控制方法. 根据混沌系统的非周期性及不可预测性, 开发一种基于混沌系统的数据加密方法. 将主混沌系统生成的伪随机序列添加到切换系统输出数据中, 能避免其经非理想网络传输时隐私的泄露. 其次, 设计一种基于粒子群优化算法的混沌形态同步控制器, 降低不确定项的影响, 保障主从混沌系统的同步性, 确保解密后数据的可用性. 然后, 利用自适应动态规划算法对采用解密后数据构造的代价函数进行优化, 将预更新最优子系统的更新规则做为候选切换律. 通过对比候选切换律与当前切换律作用下系统的性能, 将性能好的切换律做为控制策略的一部分, 确保切换系统性能最优. 最后, 通过仿真对所提方法的可行性进行验证.
- 切换系统 /
- 隐私保护 /
- 自适应动态规划 /
- 主从混沌系统 /
- 粒子群优化算法
Abstract: In control systems, for the problems of privacy leakage caused by network transmission and performance loss caused by privacy preserving, this paper studies an optimal control method with the ability of privacy preserving for switched systems. Due to the non periodicity and unpredictability of chaotic systems, a data encryption method based on which is developed. The pseudo-random sequence generated by the master chaotic system is added to the output of the switched system, which can avoid privacy leakage during transmission in non ideal network. Secondly, a chaotic morphology synchronization controller based on particle swarm optimization algorithm is designed to reduce the influence of uncertain terms, ensure the synchronization of master-slave chaotic systems, and guarantee the availability of decrypted data. Then, an adaptive dynamic programming algorithm is used to optimize the cost function based on decrypted data, and the update rule of the pre updated optimal subsystem is used as candidate switching law. By comparing the performance of the system under the action of candidate switching law and the current switching law, the better one is used as part of the control policy to ensure the optimality of the switched system performance. Finally, the feasibility of the designed method is verified through simulation.
- Switched systems /
- privacy preserving /
- adaptive dynamic programming /
- master-slave chaotic system /
- particle swarm optimization algorithm

HTML全文

图 1 PSO优化下最优切换系统的混沌数据加密

Fig. 1 Chaotic data encryption of the optimal switched systems under PSO optimization

下载: 全尺寸图片幻灯片

图 2 PSO优化过程中的适应度值

Fig. 2 Fitness values during PSO optimization process

下载: 全尺寸图片幻灯片

图 3 切换系统的状态轨迹

Fig. 3 State trajectories of switched systems

下载: 全尺寸图片幻灯片

图 8 切换系统加解密之后的误差

Fig. 8 Error of switched systems after encryption and decryption

下载: 全尺寸图片幻灯片

图 4 ADP算法优化的最优控制策略

Fig. 4 Optimal control policy optimized by ADP algorithm

下载: 全尺寸图片幻灯片

图 5 主从混沌系统的状态轨迹

Fig. 5 State trajectories of master-slave chaotic systems

下载: 全尺寸图片幻灯片

图 6 主混沌系统加密后的切换系统状态轨迹

Fig. 6 State trajectories of switched systems encrypted by master chaotic system

下载: 全尺寸图片幻灯片

图 7 从混沌系统解密后的切换系统状态轨迹

Fig. 7 State trajectories of switched systems decrypted by slave chaotic system

下载: 全尺寸图片幻灯片

参考文献(27)

[1]	Zhu Y Z, Che J X, Wu F, Chen X K, Zheng W X, Zhou D H. Stability, control and fault diagnosis of switched linear parameter varying systems: A survey. IEEE/CAA Journal of Automatica Sinica, 2025, 12(9): 1745−1761 doi: 10.1109/JAS.2025.125282
[2]	Qi Y W, Qu Z Y, Shen D. Iterative learning control for performance-driven switched systems under all unknown channel gains. Automatica, 2026, 183: Article No. 112607 doi: 10.1016/j.automatica.2025.112607
[3]	Wang K, Wu F, Sun X M. Switching anti-windup control for aircraft engines. IEEE Transactions on Industrial Electronics, 2023, 70(2): 1830−1840 doi: 10.1109/TIE.2022.3163464
[4]	Wu Z Y, Wang Y, Xiong J L, Xie M. Switching periodic event-triggered H_∞ control for NCSs and its application to UAVs. IEEE Transactions on Vehicular Technology, 2024, 73(4): 5078−5088 doi: 10.1109/TVT.2023.3336573
[5]	Ma L, Wang Y L, Han Q L. Event-triggered dynamic positioning for mass-switched unmanned marine cehicles in network environments. IEEE Transactions on Cybernetics, 2022, 52(5): 3159−3171 doi: 10.1109/TCYB.2020.3008998
[6]	Zhu Y, Peng Z H. Stabilizing design for a class of continuous-time switched linear control systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 2024, 71(8): 3900−3904 doi: 10.1109/lcsys.2023.3281757
[7]	Wang Z C, He W, Sun J, Wang G, Chen J. Event-triggered control of switched nonlinear time-delay systems with asynchronous switching. IEEE Transactions on Cybernetics, 2024, 54(7): 4348−4358 doi: 10.1109/TCYB.2023.3312491
[8]	Yang D, Li X D, Zhang G F, Lee H W J. State-dependent switching control for nonlinear impulsive switched systems with dwell time. IEEE Transactions on Automation Science and Engineering, 2025, 22: 12093−12101 doi: 10.1109/TASE.2025.3541186
[9]	Qi Y W, Zhang S M, Shi Y. Optimized active disturbance rejection control for switched systems: A triggered-learning approach. IEEE Transactions on Automatic Control, 2025, 70(9): 6347−6354 doi: 10.1109/TAC.2025.3562460
[10]	王继民, 张纪峰, 陈嘉龙. 控制系统隐私保护研究综述. 自动化学报, 2025, 51(10): 2178−2200 doi: 10.16383/j.aas.c250082 Wang Ji-Min, Zhang Ji-Feng, Chen Jia-Long. A survey of privacy protection in control systems. Acta Automatica Sinica, 2025, 51(10): 2178−2200 doi: 10.16383/j.aas.c250082
[11]	Qi Y W, Guo S T, Chi R H, Tang Y W, Qu Z Y. Privacy preserving for switched systems under robust data-driven predictive control. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025, 55(1): 480−490 doi: 10.1109/TSMC.2024.3487985
[12]	Chen W, Wang Z D, Hu J, Liu G P. Differentially private average consensus with logarithmic dynamic encoding–decoding scheme. IEEE Transactions on Cybernetics, 2023, 53(10): 6725−6736 doi: 10.1109/TCYB.2022.3233296
[13]	Qi Y W, Wang C, Zhang S W, Ahn C K. Performance-dependent privacy preserving for switched multiple systems under active disturbance rejection control. IEEE Transactions on Automation Science and Engineering, 2025, 22: 17209−17220 doi: 10.1109/TASE.2025.3583671
[14]	Qian J, Jiang H Y, Yu Y, Wang H, Miao D Q. Multi-level personalized k-anonymity privacy-preserving model based on sequential three-way decisions. Expert Systems with Applications, 2024, 239: Article No. 122343 doi: 10.1016/j.eswa.2023.122343
[15]	Hassan M U, Rehmani M H, Chen J J. Differential privacy techniques for cyber physical systems: A survey. IEEE Communications Surveys & Tutorials, 2020, 22(1): 746−789 doi: 10.1109/COMST.2019.2944748
[16]	Zhang C S, Weng J, Weng J S, Zhong Y J, Liu J N, Deng C L. Robust and secure federated learning with verifiable differential privacy. IEEE Transactions on Dependable and Secure Computing, 2025, 22(5): 5713−5729 doi: 10.1109/TDSC.2025.3574745
[17]	Carroll T L, Pecora L M. Synchronizing chaotic circuits. IEEE Transactions on Circuits and Systems, 1991, 38(4): 453−456 doi: 10.1109/31.75404
[18]	Teng L, Cao P F, Liu Y. Multi-image encryption algorithm based on novel spatiotemporal chaotic system and dynamical chaotic trajectories. IEEE Transactions on Circuits and Systems for Video Technology, 2025, 35(2): 1562−1575 doi: 10.1109/TCSVT.2024.3470110
[19]	Hou J L, Xi R, Liu P, Liu T L. The switching fractional order chaotic system and its application to image encryption. IEEE/CAA Journal of Automatica Sinica, 2017, 4(2): 381−388 doi: 10.1109/jas.2016.7510127
[20]	Wang D, Gao N, Liu D R, Li J N, Lewis F L. Recent progress in reinforcement learning and adaptive dynamic programming for advanced control applications. IEEE/CAA Journal of Automatica Sinica, 2024, 11(1): 18−36 doi: 10.1109/JAS.2023.123843
[21]	Yang Y L, Pan Y P, Xu C Z, Wunsch D C. Hamiltonian-driven adaptive dynamic programming with efficient experience replay. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(3): 3278−3290 doi: 10.1109/TNNLS.2022.3213566
[22]	Zhao B, Zhang S C, Liu D R. Self-triggered approximate optimal neuro-control for nonlinear systems through adaptive dynamic programming. IEEE Transactions on Neural Networks and Learning Systems, 2025, 36(3): 4713−4723 doi: 10.1109/TNNLS.2024.3362800
[23]	Liu M, Liu Q H, Zhang L X, Duan G R, Cao X B. Adaptive dynamic programming-based fault-tolerant attitude control for flexible spacecraft with limited wireless resources. Science China Information Sciences, 2023, 66(10): Article No. 202201 doi: 10.1007/s11432-022-3732-9
[24]	Qi Y W, Guo S T, Ahn C K, Huang J. Privacy for switched systems under MPC: A privacy-preserved rolling optimization strategy. IEEE Transactions on Cybernetics, 2025, 55(5): 2085−2097 doi: 10.1109/TCYB.2025.3549063
[25]	Kim J K, Jeong J H, Kim J h, Kim J M. ABDM: Anonymity-based big data management for protecting healthcare data from privacy breach. IEEE Network, 2025, 39(11): 298−305 doi: 10.1109/mnet.2024.3476380
[26]	Chen Y, Huang D Q, Tan S Q. Privacy-enabled secure iterative learning control of networked systems subject to disclosure attacks. IEEE Transactions on Circuits and Systems II: Express Briefs, 2024, 71(1): 196−200 doi: 10.1109/tcsii.2023.3300714
[27]	Yu X, Man Z. Fast terminal sliding-mode control design for nonlinear dynamical systems. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 2002, 49(2): 261−264 doi: 10.1109/cdc.2014.7040128