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第一作者或通信作者(*)论文
  •  Chen Jiaxi, Li Junmin, Chen Weisheng,  Zhang Shuai,Zhang Junlin. Iterative learning control for nonlinear uncertain parameterized multi-agent systems with non-identical partially unknown control directions. IEEE Transactions on Network Science and Engineering. DOI:10.1109/TNSE.2024.3371016.
  • Chen Jiaxi, Li Junmin, Chen Weisheng,  Zhang Shuai. Learning consensus of second-order unknown nonlinear parameterized multi-agent systems with periodic disturbances. IEEE Systems Journal. 2023,17(4):6357-6367.
  • Chen Jiaxi, Xie Jin, Li Junmin, Chen Weisheng, Human-in-the-loop fuzzy iterative learning control of consensus for unknown mixed-order nonlinear multi-agent systems. IEEE Transactions on Fuzzy Systems. 2024,32(1):255-265.
  • Chen Jiaxi, Li Junmin, Chen Weisheng, Gao weifeng, Neural networks-based iterative learning control consensus for periodically time-varying multi-agent systems. Science China Technological Sciences. DOI:10.1007/s11431-023-2464-1.  
  • Xie Jin, Chen Jiaxi*, Li Junmin, Chen Weisheng, Zhang Shuai. Consensus control for heterogeneous uncertain multi-agent systems with hybrid nonlinear dynamics via iterative learning algorithm. Science China Technological Sciences. DOI: 10.1007/s11431-023-2411 -2. 
  • Chen Jiaxi, Chen Weisheng, Li Junmin, Zhang Shuai. Adaptive neural control of nonlinear periodic time-varying parameterized mixed-order multi-agent systems with unknown control coefficients. Science China Technological Sciences, 2022, 65:1675-1684. 
  • Chen Jiaxi, Li Junmin, Jiao Hongwei, Zhuang Shuai. Globally fuzzy consensus of hybrid-order stochastic nonlinear multi-agent systems. ISA Transactions, 2022, 130:184-194. 
  • Chen Jiaxi, Yu ZeHua, Li Junmin, Xie Jin. Fully distributed neural control of periodically time-varying stochastic multi-agent networks with hybrid-order dynamics. Applied Mathematics and Computation, 426 (2022) 127117. 
  • Chen Jiaxi, Liu Sanyang, Li Junmin, Xie Jin. Adaptive neural tracking control for stochastic nonlinear multi-agent periodic time-varying systems, Applied Mathematical Modelling, 2022, 102: 228-242. 
  • Chen Jiaxi, Li Junmin, Guo Yaxiao, Li Jinsha. Consensus control of mixed-order nonlinear multi-agent systems: framework and case study, IEEE Transactions on Cybernetics, 2021, 52(12): 13073-13082. 
  • Chen Jiaxi, Li Junmin, Liu Sanyang, Zhao Ailiang. Adaptive neural consensus of nonlinearly parameterized multi-agent systems with periodic disturbances, ISA Transactions, 2022, 126:160-170. 
  • Chen Jiaxi, Li Junmin. Distributed consensus control of periodically time-varying multi-agent systems using neural networks and fourier series expansion, Journal of the Franklin Institute, 2021, 358(14): 7170-7186. 
  • Chen Jiaxi, Li Junmin. Distributed repetitive learning consensus control of mixed-order linear periodic parameterized nonlinear multi-agent systems, International Journal of Control, Automation and Systems, 2022, 20(3): 897-908. 
  • Zhang Shuai, Chen Jiaxi*, Bai Chan, Li Junmin. Global iterative learning control based on fuzzy systems for nonlinear multi-agent systems with unknown dynamics, Information Sciences, 2022, 587:556–571. 
  • Xie Jin, Liu Sanyang, Chen Jiaxi*, Gao Weifeng, Li Hong, Xiong Ranran, A finite time discrete distributed learning algorithm using stochastic configuration network,Information Sciences, 2022, 613: 33-49 . 
  • Chen Jiaxi, Li Junmin. Global FLS-based Consensus of Stochastic Uncertain Nonlinear Multi-agent Systems, International Journal of Automation and Computing, 2021,18(5): 826-837.
  • Xie Jin, Liu Sanyang, Chen Jiaxi*, Jia Jinping. Huber Loss Based Distributed Robust Learning Algorithm for Random Vector Functional-Link Network,Artificial Intelligence Review, DOI: 10.1007/s10462-022-10362-7. 
  • Xie Jin, Liu Sanyang, Chen Jiaxi*. A framework for distributed semi-supervised learning using single-layer feedforward networks, Machine Intelligence Research, 2022, 19, 63-74. 
  • Chen Jiaxi, Li Junmin, Yuan Xinxin. Distributed fuzzy adaptive consensus for high-order multi-agent systems with an imprecise communication topology structure. Fuzzy Sets and Systems, 2021, 402 : ‏ 1-15.
  • Chen Jiaxi, Li Junmin, Yang Nana. Globally repetitive learning consensus control of the unknown nonlinear multi-agent systems with uncertain time-varying parameters. Applied Mathematical Modelling, 2021, 89: ‏ 348-362.
  • Chen Jiaxi, Li Junmin, Yuan Xinxin. Global fuzzy adaptive consensus control of unknown nonlinear multi-agent systems. IEEE Transaction on Fuzzy Systems, 2020, 28(3): 510-522. 
  • Chen Jiaxi, Li Junmin, Zhang Rui, Wei Chengzhou. Distributed fuzzy consensus of uncertain topology structure multi-agent systems with non-identical partially unknown control directions. Applied Mathematics and Computation, 2019, 362(1):124581. 
  • Chen Jiaxi, Li Junmin, Duan Ruirui. T-S fuzzy model-based adaptive repetitive consensus control for second-order multi-agent systems with imprecise communication topology structure. Neurocomputing 2019, 331: 176-188. 
  • Chen Jiaxi, Li Junmin. Globally fuzzy leader-follower consensus of mixed-order nonlinear multi-agent systems with partially unknown direction control. Information Sciences, 2020, 523: 184-196. 
  • Chen Jiaxi, Li Junmin, Zhao Wenjie. T-S fuzzy model-based adaptive repetitive consensus control for multi-agent systems with imprecise communication topology structure. International Journal of Systems Science, 2019, 50(8): 1568-1579. 
  • Chen Jiaxi, Li Junmin, Li Jinsha, et al. T-S fuzzy model–based adaptive repetitive learning consensus control of high-order multi-agent systems with imprecise communication topology structure. International Journal of Adaptive Control and Signal Processing, 2019, 33(6): 926-942.
  • Chen Jiaxi, Li Junmin, Wu Hui. Fuzzy adaptive leader-following consensus of second-order multi-agent systems with imprecise communication topology structure. International Journal of Adaptive Control and Signal Processing, 2018, 32(6): 937-949.
  • Chen Jiaxi, Li Junmin. Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure. International Journal of Systems Science, 2018, 49(3): 546-556. 
  • Chen Jiaxi, Li Junmin, Li Jinsha. Fuzzy distributed adaptive consensus of multi-agent systems with imprecise communication topology structure. 2017 29th Chinese Control And Decision Conference (CCDC) , 2017: 4465-4469.
  • Chen, Jiaxi, Li, Junmin, Li Jinsha. Fuzzy adaptive iterative learning control for consensus of multi-agent systems with imprecise communication topology structure. 2017 6th IEEE Data Driven Control and Learning Systems Conference (DDCLS) , 2017: 54-59.  
合作论文
  • He Miao, Rong Taotao, Chen Jiaxi, Li Yafeng, Tian Dongping. Event-Triggered Nonfragile Control of Time-Varying Delays Markov Jump Systems. International Journal of Fuzzy Systems, DOI: 10.1007/s40815-024-01895-w
  • Bu Xiangwei, Luo Ruining, Chen Jiaxi, Lei Humin. Fragility-Rejection UAV Flight Control With Discrete-Time Constrained Dynamics Endowing Preselected Qualities. IEEE Journal on Miniaturization for Air and Space Systems, DOI: 10.1109/JMASS.2024.3507735. 
  • Zhang Ting, Li Ning, Chen Jiaxi. Quantized iterative learning control for nonlinear multi-agent systems with initial state error. Systems and Control Letters, Doi:10.2139/ssrn.4565136. 
  • Yang Nana, Li Junmin, Chen Jiaxi. Fully distributed hybrid adaptive learning consensus protocols for a class of non-linearly parameterized multi-agent systems. Applied Mathematics and Computation, 2020, 375: 125074. 
  • Duan Ruirui, Li Junmin, Chen Jiaxi. Mode-dependent non-fragile observer-based controller design for fractional-order T–S fuzzy systems with Markovian jump via non-PDC scheme. Nonlinear Analysis: Hybrid Systems, 2019, 34: 74-91. 
  • Wu Hui, Li Junmin, Chen Jiaxi. Distributed adaptive iterative learning consensus for uncertain topological multi-agent systems based on T-S fuzzy models. International Journal of Fuzzy Systems, 2018, 20(8): 2605-2619. 
  • Yang Nana, Li Junmin, Chen Jiaxi. Leader-following consensus of multi-agent systems with uncertain weight coupling topological graph using distributed adaptive iterative learning control, 2019 Chinese Control Conference (CCC), 2019: 5568-5573.