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Real-Time Implementation of Neuro Adaptive Observer-Based Robust Backstepping Controller for Twin Rotor Control System

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Abstract

In this paper, a robust backstepping controller based on the neuro adaptive observer for the twin rotor multiple-input-multiple-output (MIMO) system is designed and implemented in real time. The twin rotor MIMO system (TRMS) belongs to a class of nonlinear uncertain system having unstable, coupled dynamics. Nonlinearities of the TRMS are estimated using Chebyshev neural network. A tuning scheme based on Lyapunov theory of stability is developed which can guarantee the boundedness of tracking error and weights of the neural network. The proposed observer-based control guarantees the stability of the closed-loop adaptive system and the tracking errors converge to small residual sets in the presence of constraints on the control input. The effectiveness of the proposed observer-based robust controller is illustrated through simulation and experimental results. The real time implementation has been carried out on the real-time TRMS using MATLAB real-time tool box and Advantech PCI1711 card.

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Acknowledgments

The authors acknowledge the contribution of Department of Science and Technology, Government of India, New Delhi, India through Project SR/S3/EECE/004/2008.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology, Kurukshetra, India

    Bhanu Pratap

  2. Department of Electrical Engineering, M. N. National Institute of Technology, Allahabad, India

    Shubhi Purwar

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  1. Bhanu Pratap
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  2. Shubhi Purwar
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Correspondence to Bhanu Pratap.

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Pratap, B., Purwar, S. Real-Time Implementation of Neuro Adaptive Observer-Based Robust Backstepping Controller for Twin Rotor Control System. J Control Autom Electr Syst 25, 137–150 (2014). https://doi.org/10.1007/s40313-013-0098-y

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  • DOI: https://doi.org/10.1007/s40313-013-0098-y

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