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【IEEE/CAA JAS虚拟专题】非线性系统
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本期精选2022年至今已发表部分非线性系统相关文章，欢迎阅览！
K. Zhao, C. Y. Wen, Y. D. Song, and F. L. Lewis, “Adaptive uniform performance control of strict-feedback nonlinear systems with time-varying control gain,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 451–461, Feb. 2023. doi: 10.1109/JAS.2022.106064
> Proposed control is flexible to handle the global or symmetric semi-global performance cases uniformly just by selecting the initial value of the time-varying scaling function properly, making the controller re-design and stability re-analysis not required.
> By defining an ENF and imposing a condition on the update law of Nussbaum argument, the developed control relaxes the complicated calculation and proof in the existing results.
> By extracting the core function information from the non- parametric uncertainty, no approximator is required, despite unknown control directions.
F. Tatari, H. Modares, C. Panayiotou, and M. Polycarpou, “Finite-time distributed identification for nonlinear interconnected systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 7, pp. 1188–1199, Jul. 2022. doi: 10.1109/JAS.2022.105683
> A novel finite-time distributed identification method is introduced for nonlinear interconnected systems using concurrent learning.
> Concurrent learning approach continually minimizes the identification error for a batch of previously recorded data collected from each subsystem as well as its neighboring subsystems.
> State information of neighboring interconnected subsystems is acquired through direct communication.
X. Lyu and Z. Lin, "PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation," IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 90-98, Jan. 2022. doi: 10.1109/JAS.2021.1004281
> PID control design for planar nonlinear uncertain systems with input saturation.
> Robustness with respect to uncertain nonlinearities.
> Maximization of the domain of attraction and output tracking capacity.
C. H. Zhang, L. Chang, L. T. Xing, and X. F. Zhang, “Fixed-time stabilization of a class of strict-feedback nonlinear systems via dynamic gain feedback control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 403–410, Feb. 2023. doi: 10.1109/JAS.2023.123408
> Presents a novel fixed-time stabilization control method for a class of strict-feedback nonlinear systems involving unmodelled system dynamics.
> Compared with existing results, the ``explosion of complexity" problem of backstepping control is avoided.
> Proposed controller is still valid beyond the given fixed-time convergence instant.
G. Q. Zhu, H. Q. Li, X. Y. Zhang, C. L. Wang, C.-Y. Su, and J. P. Hu, “Adaptive consensus quantized control for a class of high-order nonlinear multi-agent systems with input hysteresis and full state constraints,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 9, pp. 1574–1589, Sept. 2022. doi: 10.1109/JAS.2022.105800
> Quantized control method of the hysteretic multi-agent systems is considered and a hysteresis quantization inverse compensator is established.
> First study to apply the barrier Lyapunov function to the hysteretic multi-agent systems.
> Quantized control strategy constructed only requires quantizer to have sector bounded property.
A. J. Song, G. H. Wu, W. Pedrycz, and L. Wang, "Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems," IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 75-89, Jan. 2022. doi: 10.1109/JAS.2021.1004278
> Variable reduction strategy was proposed to reduce nonlinear equations systems.
> A framework of variable reduction strategy and evolutionary algorithms was presented.
> Variable reduction strategy enables a better performance of an original algorithm.
B. Niu, J. D. Liu, D. Wang, X. D. Zhao, and H. Q. Wang, "Adaptive Decentralized Asymptotic Tracking Control for Large-Scale Nonlinear Systems With Unknown Strong Interconnections," IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 173-186, Jan. 2022. doi: 10.1109/JAS.2021.1004246
> Decentralized control scheme proposed removes all the two widely adopted traditional conditions of the interconnected terms by using the inherent properties of Gaussian function and thereby deals with completely unknown strong interconnections successfully.
> Asymptotic tracking control is realized even though the uncertain parameters, large-scale system structure and unknown strong interconnections are considered.
> By applying the DSC technology, the inherent “explosion of complexity” problem in backstepping is eliminated.
Y. H. Wang, X. D. Li, and S. J. Song, “Input-to-state stabilization of nonlinear impulsive delayed systems: An observer-based control approach,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 7, pp. 1273–1283, Jul. 2022. doi: 10.1109/JAS.2022.105422
> Problems of input-to-state stabilization for impulsive delayed systems are addressed.
> A novel observer-based output feedback controller is designed for stabilization.
> Designed state observer can be applied to the case involving unmeasurable time delays.
J. Mao, X. Meng, and D. Ding, “Fuzzy set-membership filtering for discrete-time nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 1026–1036, Jun. 2022. doi: 10.1109/JAS.2022.105416
> An improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy rule.
> Two types of fuzzy set-membership filters are proposed to effectively improve filtering performance.
> Proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.
Z. N. Pang, X. S. Si, C. H. Hu, and Z. X. Zhang, “An age-dependent and state-dependent adaptive prognostic approach for hidden nonlinear degrading system,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 907–921, May 2022. doi: 10.1109/JAS.2021.1003859
> Influence of the degradation rate change among different units is explicitly considered.
> An age- and state-dependent nonlinear degradation model considering the unit-to-unit variability is proposed.
> Uncertainty of the hidden state from the observations is incorporated into the RUL estimation.
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