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Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
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Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
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Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay

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Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay
Journal Article

Design of Optimal Disturbance Attenuation Controller for Networked T–S Fuzzy Vehicle Active Suspension with Control Delay

2019
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Overview
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.