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Efficient learning control of uncertain nonlinear systems with input constraints: a disturbance observer-based neural network approach

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Abstract

To deal with the effects of the input saturation and time-varying input delay, this article presents a serial-parallel identifier-based composite neural network learning control for uncertain nonlinear systems subject to external disturbances. Based on the backstepping technique, a radial basis function network is adopted to identify the unknown term, where the neural network learning accuracy is studied by considering a modeling error. In addition, a compensation system is designed to cope with input delay and input saturation, simultaneously. Besides, the explosion of complexity is mitigated by employing the command-filtered control approach. To enhance the robust performance of the overall system, the proposed control structure is enriched by a disturbance observer. Therefore, new adaptive rules are constructed. The stability of the closed-loop system is ensured by the Lyapunov theorem. Simulation results clarify the efficiency of the proposed control algorithm.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, 36199-95161, Iran

    Javad Keighobadi & Alireza Alfi

  2. Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, 15916-34311, Iran

    Ali Mehrjouyan

Authors
  1. Javad Keighobadi
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  2. Ali Mehrjouyan
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  3. Alireza Alfi
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Contributions

Javad Keighobadi:Problem formulation; Control design; Writing-original draft; Writing-revised manuscript Ali Mehrjouyan: Data analysis; Software; Updating Software; Validation Alireza Alfi: Conceptualization; Writing-original draft; Writing- revised manuscript; Validation

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Correspondence to Javad Keighobadi.

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Keighobadi, J., Mehrjouyan, A. & Alfi, A. Efficient learning control of uncertain nonlinear systems with input constraints: a disturbance observer-based neural network approach. Int. J. Dynam. Control (2024). https://doi.org/10.1007/s40435-024-01416-5

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  • DOI: https://doi.org/10.1007/s40435-024-01416-5

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