International Journal of Fuzzy Systems

, Volume 21, Issue 2, pp 676–684 | Cite as

Design of Optimal Disturbance Attenuation Controller for Networked TS Fuzzy Vehicle Active Suspension with Control Delay

  • Xiao-Fang Zhong
  • Shi-Yuan Han
  • Jin ZhouEmail author
  • Yue-Hui Chen


In this paper, a disturbance attenuation controller is presented for networked vehicle active suspension with measurement noise and random control delay. By defining the appearing probabilities of control delay as the membership function, the Takagi–Sugeno (TS) fuzzy model of networked vehicle active suspension is established with the consideration of the persistent irregular road disturbance, the random actuator delay, and the measurement noise. By designing a transformation vector, the disturbance attenuation control problem is reformulated as an equivalence two-point-boundary-value problem under the constrains of a delay-free system with respect to an equivalence performance index. After that, an optimal disturbance attenuation controller is proposed by solving a Riccati equation and a Stein equation, in which a Kalman filter is employed to estimate the road disturbance state with Gaussian white noise. Finally, by employing a simple vehicle active suspension, simulation results show that the designed controller can attenuate the vibration and compensate the control delay for the networked TS fuzzy vehicle active suspension, in which the values of the sprung mass acceleration, the suspension deflection and the tyre deflection can be reduced effectively.


Vehicle active suspension Disturbance attenuation control TS fuzzy control Control delay Optimal control 



This work is supported by the Natural Science Foundation of Shandong Province (ZR2017MF044), the Shandong Province Key Research and Development Program (2018GGX101016, 2018GGX101048, 2017GGX10144), the Shandong Province Higher Educational Science and Technology Program (J17KA047, J16LN07, J16LB06, J15LN13), the Natural Science Foundation of China (61671220, 61702217).


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Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xiao-Fang Zhong
    • 1
    • 2
  • Shi-Yuan Han
    • 1
    • 2
  • Jin Zhou
    • 2
    Email author
  • Yue-Hui Chen
    • 2
  1. 1.School of Data and Computer ScienceShandong Women’s UniversityJinanChina
  2. 2.Shandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinanChina

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