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Volume 6 Issue 6
Nov.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2019  >  6(6): 1519-1527
Mohammad Javad Mahmoodabadi and Saideh Arabani Mostaghim, "Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming," IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1519-1527, Nov. 2019. doi: 10.1109/JAS.2017.7510388
Citation: Mohammad Javad Mahmoodabadi and Saideh Arabani Mostaghim, "Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming," IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1519-1527, Nov. 2019. doi: 10.1109/JAS.2017.7510388
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Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming

doi: 10.1109/JAS.2017.7510388
  • 1.

    Department of Mechanical Engineering, Sirjan University of Technology, Sirjan 9306118541, Iran

  • 2.

    Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht 3756, Iran

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    Abstract
  • In this paper, at first, the single input rule modules (SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multi-objective particle swarm optimization (MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms. Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internet-based control.

     

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    Highlights

    • A novel multi-objective particle swarm optimization was introduced
    • The leader selection method was based on density measures, the personal best positions were determined via Sigma method, the dynamic elimination technique was applied to prune the archive, and the turbulence operator was utilized to escape from the local minima.
    • An optimal fuzzy controllers was designed for the double inverted pendulum system.
    • The modeling, control and stability simulation of the double inverted pendulum system were presented on the net using Java Applets with educational goals.

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