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Challenging simulation practice (failure and success) on implicit tracking control of double-integrator system via Zhang-gradient method

Author

Listed:
  • Zhang, Yunong
  • Zhai, Keke
  • Chen, Dechao
  • Jin, Long
  • Hu, Chaowei

Abstract

Zhang-gradient (ZG) method is a combination of Zhang dynamics (ZD) and gradient dynamics (GD) methods which are two powerful methods for online time-varying problems solving. ZG controllers are designed using the ZG method to solve the tracking control problem of a certain system. In this paper, the design process of the ZG controllers with explicit as well as implicit tracking control of the double-integrator system is presented in detail. In addition, the corresponding computer simulations are conducted with different values of the design parameter λ to illustrate the effectiveness of ZG controllers. However, even though the ZG controllers are powerful, there is still a challenge in the simulation practice. Specifically, different settings of simulation options in MATLAB ordinary differential equation (ODE) solvers may lead to different simulation results (e.g., failure and success). For better comparison, the successful and failed simulation results are both presented. The differences in simulation results remind us to pay more attention to MATLAB defaults and options when we conduct such simulations.

Suggested Citation

  • Zhang, Yunong & Zhai, Keke & Chen, Dechao & Jin, Long & Hu, Chaowei, 2016. "Challenging simulation practice (failure and success) on implicit tracking control of double-integrator system via Zhang-gradient method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 120(C), pages 104-119.
    • Handle: RePEc:eee:matcom:v:120:y:2016:i:c:p:104-119
    DOI: 10.1016/j.matcom.2015.07.002
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    References listed on IDEAS

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    1. Frechard, J. & Knittel, D. & Dessagne, P. & Pellé, J.S. & Gaudiot, G. & Caspar, J.C. & Heitz, G., 2013. "Modelling and fast position control of a new unwinding–winding mechanism design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 90(C), pages 116-131.
    2. Yi, Chenfu & Zhang, Yunong & Guo, Dongsheng, 2013. "A new type of recurrent neural networks for real-time solution of Lyapunov equation with time-varying coefficient matrices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 92(C), pages 40-52.
    3. El Fadil, H. & Giri, F. & Guerrero, Josep M., 2013. "Adaptive sliding mode control of interleaved parallel boost converter for fuel cell energy generation system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 193-210.
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