Experimental implementation of nonlinear TORA system and adaptive backstepping controller design

Ching Hung Lee*, Sheng Kai Chang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


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 ABC WNN 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 ABC WNN 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.

Original languageEnglish
Pages (from-to)785-800
Number of pages16
JournalNeural Computing and Applications
Issue number4
StatePublished - Jun 2012


  • Adaptive
  • Backstepping
  • Lyapunov theorem
  • Nonlinear control
  • Wavelet neural network

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