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This paper focuses on the fuzzy guaranteed cost H ∞ control problem for uncertain nonlinear vehicle active suspension system with random actuator time delay. Its main contribution to the literature is that a fuzzy guaranteed cost H ∞ controller (FGCHC) is proposed to ensure the resulting closed-loop vehicle active suspension system to be asymptotically stable and guarantee the performance index to be less than a preset upper bound. More specifically, taking the varying masses and the uncertainties caused by random actuator delay into consideration, a discrete-time Takagi-Sugeno fuzzy model for vehicle active suspension is obtained based on an augmented vector, which is without explicit of random actuator delay. By employing the Lyapunov stability theory and the linear matrix inequality (LMI) approach, the existence condition and the design approach for proposed FGCHC are presented. Meanwhile, the computability for proposed FGCHC is guaranteed by solving a corresponding convex optimization problem. By analyzing performance requirements for vehicle active suspension under different simulation scenarios, simulation results demonstrate that the proposed FGCHC can offset the vibration and compensate the varying masses and uncertainties for vehicle active suspension effectively. [ABSTRACT FROM AUTHOR]

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 (T–S) 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 T–S fuzzy vehicle active suspension, in which the values of the sprung mass acceleration, the suspension deflection and the tyre deflection can be reduced effectively. [ABSTRACT FROM AUTHOR]