Optimal FLC-Sugeno Controller based on PSO for an Active Damping System

Authors

  • Hoang Viet Nguyen School of Automation Science and Engineering, South China University of Technology, China
  • Feiqi Deng School of Automation Science and Engineering, South China University of Technology, China
  • Tien-Duy Nguyen Thai Nguyen University of Technology, Vietnam
Volume: 14 | Issue: 1 | Pages: 12769-12774 | February 2024 | https://doi.org/10.48084/etasr.6662

Abstract

In this paper, a method for the design of an optimal Sugeno model (FLC-Sugeno) fuzzy logic controller for the active suspension system of quarter-vehicle models is presented. The parameters of the FLC-Sugeno controller are optimally searched, using the Particle Swarm Optimization (PSO) algorithm. The 16 optimized parameters include 3 parameters for adjusting the domain of the input state variables and control variables at the controller’s output, 4 fuzzy set adjustment numbers of the linguistic variables, and 9 parameters as the fuzzy rule weights of the rule system control. To compare and evaluate the effectiveness of the optimal FLC-Sugeno controller, an optimal PID controller using PSO is also implemented. Simulation results of the active damping system with the controllers when affected by the same type and standard road surface excitation show that the FLC-Sugeno controller is optimal for the quick ending of the oscillations of vehicle body displacement. The result shows that the proposed controlling scheme can be extended and applied to more complex active damping system models.

Keywords:

FLC-Sugeno, particle swarm optimization, active suspension system, quarter-vehicle models

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References

R. Pekgökgöz, M. Gurel, M. Bilgehan, and M. Kisa, "Active suspension of cars using fuzzy logic controller optimized by genetic algorithm," International Journal of Engineering and Applied Sciences, vol. 2, no. 4, pp. 27–37, Jan. 2010.

E. Allam, H. F. Elbab, M. A. Hady, and S. Abouel-Seoud, "Vibration Control of Active Vehicle Suspension System Using Fuzzy Logic Algorithm," Fuzzy Information and Engineering, vol. 2, no. 4, pp. 361–387, Dec. 2010.

N. Changizi and M. Rouhani, "Comparing Pid And Fuzzy Logic Control A Quarter-car Suspension System," Journal of Mathematics and Computer Science, vol. 2, no. 3, pp. 559–564, Apr. 2011.

Z. Chen, "Research on fuzzy control of the vehicle’s semi-active suspension," in Research on fuzzy control of the vehicle’s semi-active suspension, Jun. 2015, pp. 631–636.

S. Palanisamy and S. Karuppan, "Fuzzy control of active suspension system," Journal of Vibroengineering, vol. 18, no. 5, pp. 3197–3204, Aug. 2016.

Instrumentation and Control Engg., Dr. B.R. AmbedkarNational Institute of Tech., Jalandhar, India, N. S. Bhangal, and K. A. Raj, "Fuzzy Control of Vehicle Active Suspension System," in International Journal of Mechanical Engineering and Robotics Research., 2016.

A. A. Basari, N. a. A. Nawir, K. A. Mohamad, X. Y. Ng, and A. M. Khafe, "Fuzzy Logic Controller for Half Car Active Suspension System," Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 10, no. 2, pp. 125–129, May 2018.

S.-Y. Han, J.-F. Dong, J. Zhou, and Y.-H. Chen, "Adaptive Fuzzy PID Control Strategy for Vehicle Active Suspension Based on Road Evaluation," Electronics, vol. 11, no. 6, Jan. 2022, Art. no. 921.

H. Medjoubi, A. Yassine, and H. Abdelouahab, "Design and Study of an Adaptive Fuzzy Logic-Based Controller for Wheeled Mobile Robots Implemented in the Leader-Follower Formation Approach," Engineering, Technology & Applied Science Research, vol. 11, no. 2, pp. 6935–6942, Apr. 2021.

N. Zerroug, K. Behih, Z. Bouchama, and K. Zehar, "Robust Adaptive Fuzzy Control of Nonlinear Systems," Engineering, Technology & Applied Science Research, vol. 12, no. 2, pp. 8328–8334, Apr. 2022.

J. Joshua Robert, P. Senthil Kumar, S. Tushar Nair, D. H. Sharne Moni, and B. Swarneswar, "Fuzzy control of active suspension system based on quarter car model," Materials Today: Proceedings, vol. 66, pp. 902–908, Jan. 2022.

N. E. H. Yazid, K. Hartani, A. Merah, and T. M. Chikouche, "New Fuzzy Logic Control for Quarter Vehicle Suspension System," in Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities, 2022, pp. 643–652.

T. A. Arslan, F. E. Aysal, İ. Çeli̇k, H. Bayrakçeken, and T. N. Öztürk, "Quarter Car Active Suspension System Control Using Fuzzy Controller," Engineering Perspective, vol. 2, no. 4, pp. 33–39, Dec. 2022.

Z. Zhang and J. Dong, "A New Optimization Control Policy for Fuzzy Vehicle Suspension Systems Under Membership Functions Online Learning," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 5, pp. 3255–3266, Feb. 2023.

I. H. Hamad, A. Chouchaine, and H. Bouzaouache, "A Takagi-Sugeno Fuzzy Model for Greenhouse Climate," Engineering, Technology & Applied Science Research, vol. 11, no. 4, pp. 7424–7429, Aug. 2021.

N. V. Hai, N. V. Tiem, L. H. Lan, and T. H. Vo, "Pantograph Catenary Contact Force Regulation Based on Modified Takagi-Sugeno Fuzzy Models," Engineering, Technology & Applied Science Research, vol. 13, no. 1, pp. 9879–9887, Feb. 2023.

T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-15, no. 1, pp. 116–132, Jan. 1985.

J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proceedings of ICNN’95 - International Conference on Neural Networks, Perth, WA, Australia, Aug. 1995, vol. 4, pp. 1942–1948.

G. P. A. Koch, "Adaptive Control of Mechatronic Vehicle Suspension Systems," Ph.D. dissertation, Technical University of Munich, Munich, Germany, 2011.

B. C. Murphy, "Design and construction of a precision tubular linear motor and controller," M.S. thesis, Texas A&M University, 2003.

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How to Cite

[1]
H. V. Nguyen, F. Deng, and T.-D. Nguyen, “Optimal FLC-Sugeno Controller based on PSO for an Active Damping System”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 1, pp. 12769–12774, Feb. 2024.

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