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Volume 11 Issue 5
May  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(5): 1213-1226
Z. Chen, S. Zhou, C. Shen, L. Lyu, J. Zhang, and  B. Yao,  “Observer-based adaptive robust precision motion control of a multi-joint hydraulic manipulator,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1213–1226, May 2024. doi: 10.1109/JAS.2024.124209
Citation: Z. Chen, S. Zhou, C. Shen, L. Lyu, J. Zhang, and  B. Yao,  “Observer-based adaptive robust precision motion control of a multi-joint hydraulic manipulator,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1213–1226, May 2024. doi: 10.1109/JAS.2024.124209
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Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

doi: 10.1109/JAS.2024.124209
Funds:  This work was supported by the National Natural Science Foundation of China (52075476, 52105065, 92048302), Zhejiang Provincial Natural Science Foundation of China (LR23E050001), and the Science and Technology Program of Hebei (E2021210011)
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    Abstract

  • Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks. However, when faced with a complex operation, the traditional proportional-integral-derivative (PID) control may not meet requirements for high control performance. Model-based full-state-feedback control is an effective alternative, but the states of a hydraulic manipulator are not always available and reliable in practical applications, particularly the joint angular velocity measurement. Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement, the low-pass filtering is commonly used, but it will definitely restrict the closed-loop bandwidth of the whole system. To avoid this problem and realize better control performance, this paper proposes a novel observer-based adaptive robust controller (obARC) for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement. Specifically, a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties. Then, the adaptive robust control is developed to compensate for the dynamic uncertainties, and the close-loop system robust stability is theoretically proved under the observation and control errors. Finally, comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods, specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough, which is limited by low-pass filtering in full-state-feedback control.

     

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    Highlights

    • Not like the velocity state in traditional observers, the velocity-related intermediate state is observed according to the adaptive model parameters of the hydraulic manipulator in this paper. In this way, the observer is able to take the model uncertainties into consideration through online parameter adaptation
    • Apart from the observed object states being different, obARC does not require accurate observation results, but rather focuses on combining the differential equation of state observation with the intermediate steps of controller design, thereby eliminating the dependence of the control effect on the observation accuracy and achieving the goal of further improving the final control accuracy
    • The controller designed in this paper can theoretically prove the stability of the closed-loop system in the presence of model parameter uncertainty, uncertain nonlinearity, observation errors, and other factors
    • The designed controller can achieve the performance improvement by comparison with the traditional methods, especially with better control accuracy due to the closed-loop bandwidth breakthrough which is limited by low-pass filtering in full-state-feedback control. The proposed method is significant for hydraulic manipulators used in some harsh environments and unable to be equipped with various of accurate sensors

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