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Experimental implementation of nonlinear TORA system and adaptive backstepping controller design

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Abstract

The purpose of this paper is to design an adaptive controller and system experimental implementation for nonlinear translational oscillations with a rotational actuator (TORA) system. A wavelet-based neural network (WNN) is proposed to develop an adaptive backstepping control scheme, called ABCWNN for TORA system. To ensure the stability of the controlled system, a compensated controller is designed to enhance the control performance. Based on its universal approximation ability, we use a WNN to estimate the system uncertainty including frictional forces, external disturbance, and parameter variance. According to the estimations of the WNNs, the ABCWNN control is developed via a backstepping design procedure such that the system outputs follow the desired trajectories. For system development, the effects of frictional forces are discussed and solved using the estimation of the WNN. The effectiveness of the proposed control scheme for TORA system is verified by numerical simulation and experimental results.

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Acknowledgments

The authors would like to thank the Associate Editor and anonymous reviewers for their insightful comments and valuable suggestions. This work was supported in part by the National Science Council, Taiwan, R.O.C., under contracts NSC-95-2221-E-155-068-MY2.

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Authors and Affiliations

  1. Department of Electrical Engineering, Yuan Ze University, Chungli, Taoyuan, Taiwan, Republic of China

    Ching-Hung Lee & Sheng-Kai Chang

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  1. Ching-Hung Lee
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  2. Sheng-Kai Chang
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Correspondence to Ching-Hung Lee.

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Lee, CH., Chang, SK. Experimental implementation of nonlinear TORA system and adaptive backstepping controller design. Neural Comput & Applic 21, 785–800 (2012). https://doi.org/10.1007/s00521-010-0515-0

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