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Volume 12 Issue 11
Nov.  2025

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  >  12(11): 2286-2299
J. Zhu, S. Yuan, L. Mou, J. Luo, and H. Pu, “Adaptive periodic disturbance compensation for continuous-time linear systems with input delays,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 11, pp. 2286–2299, Nov. 2025. doi: 10.1109/JAS.2025.125258
Citation: J. Zhu, S. Yuan, L. Mou, J. Luo, and H. Pu, “Adaptive periodic disturbance compensation for continuous-time linear systems with input delays,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 11, pp. 2286–2299, Nov. 2025. doi: 10.1109/JAS.2025.125258
shu

Adaptive Periodic Disturbance Compensation for Continuous-Time Linear Systems With Input Delays

doi: 10.1109/JAS.2025.125258
Funds:  This work was supported in part by the National Natural Science Foundation of China (62325302, 62203076, 62103065, 62033001, 62303079), the China Postdoctoral Science Foundation (2021M700584), the Natural Science Foundation of Chongqing, China (cstc2020jcyj-zdxmX0014), and the Program of Shanghai Academic/Technology Research Leader (21XD1421400)
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    Abstract
  • Unknown time-varying periodic disturbances and input delays can degrade control performance and even lead to system instability. This paper presents a novel direct adaptive output feedback controller based on the internal model principle (IMP) to compensate for the unknown time-varying periodic disturbance in input delay systems. To reduce the design difficulty of the controller, the input delay system is equivalent to an input delay-free system by constructing stable auxiliary systems. Next, all the stabilizing controllers of the input delay system are derived by using the Youla parameterization method. Based on the IMP, an interpolation condition to completely compensate for periodic disturbances is formulated. Then, to compensate for the unknown time-varying periodic disturbance, a parameter adaptive algorithm is designed to update the Q-parameters online. The convergence of adaptive algorithms is analyzed by the Lyapunov function theory. Simulation and experimental results validated the effectiveness of the proposed method.

     

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