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Volume 7 Issue 3
Apr.  2020

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Dailin Zhang, Zining Wang and Masayoshi Tomizuka, "A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 693-701, May 2020. doi: 10.1109/JAS.2020.1003135
Citation: Dailin Zhang, Zining Wang and Masayoshi Tomizuka, "A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 693-701, May 2020. doi: 10.1109/JAS.2020.1003135

A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control

doi: 10.1109/JAS.2020.1003135
Funds:  This work was supported in part by the National Natural Science Foundation of China (51775215, 51535004)
More Information
  • Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parameter-model-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.

     

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    Highlights

    • A variable parameter model is proposed to describe a variable parameter system.
    • A multi-step adaptive seeking approach is used to obtain parameters of a variable parameter model in real time.
    • A variable-parameter-model-based feedforward compensation method is proposed to achieve smaller tracking errors than a traditional feedforward compensation method.
    • Theoretical analysis and simulation results show that the variable-parameter-model-based feedforward compensation can obtain better performance than a traditional feedforward compensation.

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