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Volume 9 Issue 5
May  2022

IEEE/CAA Journal of Automatica Sinica

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K. H. He, C. Y. Dong, and  Q. Wang,  “Active disturbance rejection control for uncertain nonlinear systems with sporadic measurements,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 893–906, May 2022. doi: 10.1109/JAS.2022.105566
Citation: K. H. He, C. Y. Dong, and  Q. Wang,  “Active disturbance rejection control for uncertain nonlinear systems with sporadic measurements,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 893–906, May 2022. doi: 10.1109/JAS.2022.105566

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

doi: 10.1109/JAS.2022.105566
Funds:  This work was supported by the National Natural Science Foundation of China (61833016, 61873295)
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  • This paper deals with the problem of active disturbance rejection control (ADRC) design for a class of uncertain nonlinear systems with sporadic measurements. A novel extended state observer (ESO) is designed in a cascade form consisting of a continuous time estimator, a continuous observation error predictor, and a reset compensator. The proposed ESO estimates not only the system state but also the total uncertainty, which may include the effects of the external perturbation, the parametric uncertainty, and the unknown nonlinear dynamics. Such a reset compensator, whose state is reset to zero whenever a new measurement arrives, is used to calibrate the predictor. Due to the cascade structure, the resulting error dynamics system is presented in a non-hybrid form, and accordingly, analyzed in a general sampled-data system framework. Based on the output of the ESO, a continuous ADRC law is then developed. The convergence of the resulting closed-loop system is proved under given conditions. Two numerical simulations demonstrate the effectiveness of the proposed control method.


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    • Expand the application scope of ADRC. This paper is the first attempt of ADRC application in sporadic-in-measurement systems. The structure of the proposed ADRC is developed, in which a predictor-based continuous time observer executes state and uncertainty estimation based on intermittent measurements
    • New methodology for state estimation with sampled measurements. Different from all existing estimation techniques for systems with sampled measurements, the proposed ESO does not require the knowledge of the nonlinear dynamics and eliminates some restriction on the system nonlinearity
    • Rigorous convergence proofs for both the ESO and the closed-loop systems
    • Implementation consideration. We provide algorithms and explanations on how to design various parameters in the ADRC architecture. A simulation on the control of flexible robot manipulator is carried out to verify the effectiveness


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