Optimal Vibration Control for Vehicle Active Suspension Discrete‐Time Systems with Actuator Time Delay

Han, Shiyuan; Tang, Gong‐You; Chen, Yuehui; Yang, Xi-Xin; Yang, Xue

doi:10.1002/asjc.719

Cited by 37 publications

(36 citation statements)

References 21 publications

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“…Assume that the system is controlled by the following control law:

u false(t false) = K x false(t false),

where K =[2.81 −363.43 −162.48 −9.17] is the state feedback gain matrix and the actuator time‐delay satisfies 0.1 ≤ τ ( t ) ≤ 0.2. The detailed description of designing the state feedback control law for a quarter‐car suspension system with actuator time‐delay can be found in other works . By using the zero‐order hold method with the sampling period T s , the discrete‐time state‐space model of the closed‐loop system can be described in the form of with the following parameters:

\begin{matrix} alignleft \\ align-1 & align-2 A = [\begin{array}{cccc} 0.4160 & 0.9923 & 0.0622 & 0.0097 \\ 0.4454 & - 0.1514 & 0.0276 & - 0.0053 \\ - 2.3146 & - 3.8502 & 0.7653 & 0.0382 \\ - 3.2122 & 4.7387 & 0.4083 & - 0.5138 \end{array}], A_{d} = [\begin{array}{cccc} 0 & - 0.005 & - 0.0022 & - 0.0001 \\ 0 & 0.0038 & 0.0017 & 0.0001 \\ 0.0002 & - 0.0197 & - 0.0088 & - 0.0005 \\ 0.0002 & - 0.0273 & - 0.0122 & - 0.0007 \end{array}] \\ align-1 & align-2 B = [\begin{array}{cc}  \end{array}] \end{matrix}

…”

Section: Simulation Resultsmentioning

confidence: 99%

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Hedayati

Rahmani

2019

Intl J Robust & Nonlinear

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Summary In this paper, the problem of robust distributed H∞ filtering is investigated for state‐delayed discrete‐time linear systems over a sensor network with multiple fading measurements, random time‐varying communication delays, and norm‐bounded uncertainties in all matrices of the system. The diagonal matrices, whose elements are individual independent random variables, are utilized to describe the multiple fading measurements. Furthermore, the Bernoulli‐distributed white sequences are introduced to model the random occurrence of time‐varying communication delays. In the proposed filtering approach, the stability of the estimation error system is first shown by the Lyapunov stability theory and the H∞ performance is then achieved using a linear matrix inequality method. Finally, two numerical examples are given to show the effectiveness and performance of the proposed approach.

show abstract

“…Assume that the system is controlled by the following control law:

u false(t false) = K x false(t false),

\begin{matrix} alignleft \\ align-1 & align-2 A = [\begin{array}{cccc} 0.4160 & 0.9923 & 0.0622 & 0.0097 \\ 0.4454 & - 0.1514 & 0.0276 & - 0.0053 \\ - 2.3146 & - 3.8502 & 0.7653 & 0.0382 \\ - 3.2122 & 4.7387 & 0.4083 & - 0.5138 \end{array}], A_{d} = [\begin{array}{cccc} 0 & - 0.005 & - 0.0022 & - 0.0001 \\ 0 & 0.0038 & 0.0017 & 0.0001 \\ 0.0002 & - 0.0197 & - 0.0088 & - 0.0005 \\ 0.0002 & - 0.0273 & - 0.0122 & - 0.0007 \end{array}] \\ align-1 & align-2 B = [\begin{array}{cc}  \end{array}] \end{matrix}

…”

Section: Simulation Resultsmentioning

confidence: 99%

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Hedayati

Rahmani

2019

Intl J Robust & Nonlinear

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“…As stated in , the following finite sum of fourier series describes the road displacement input

z_{r} (t) = {falsefalse}_{\sum}^{j = 1} ξ_{j} (t) = {falsefalse}_{\sum}^{j = 1} φ_{j} \sin (j ω_{0} t + θ_{j}),

where

φ_{j} = \sqrt{2 G_{d} (j normalΔ normal Ω) normalΔ normal Ω}

, ΔΩ = 2 π / l , the initial phase θ j ∈[0,2 π ) is a random variable,

p \in ((], \begin{matrix} array (ω_{2} - ω_{1}) / ω_{0} + 1, & array (ω_{2} - ω_{1}) / ω_{0} + 2 \end{matrix})

is used to restrict the range of frequency with

[ω_{1}, ω_{2}] = ([], β_{1} \sqrt{{k_{s} / m}_{s}}, β_{2} \sqrt{{k_{s} / m}_{s}})

, where 0 < β 1 < 1 < β 2 ,

ω_{n} = \sqrt{k_{s} / m_{s}}

, and l is the length of road segment.…”

Section: Problem Formulationmentioning

confidence: 99%

Approximation Optimal Vibration for Networked Nonlinear Vehicle Active Suspension with Actuator Time Delay

Han

Zhang

Tang

2017

Asian Journal of Control

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This paper is concerned with the modelling and vibration control problem for networked nonlinear vehicle active suspension (NNVAS) with actuator time delay. Inserting in‐vehicle communication network to active suspension, a novel model for NNVAS is established based on the Takagi‐Sugeno fuzzy fusion technology first. By introducing a transformation vector, NNVAS with actuator time delay is reformed as a delay‐free nonlinear system. Then, an approximation optimal vibration controller (AOVC) is proposed by using an iterative algorithm, which consists of suspension state item, a road disturbance state item, and a compensated item for nonlinear response. Dependant on the control performance in each iteration, the computability of proposed AOVC is realized. A reduced‐order observer is designed to solve the physical unrealizable problem of road disturbances. Finally, compared with the open‐loop system and H∞ control scheme without network setting, the capability of improving control performance under AOVC is illustrated.

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“…Han et al . apply optimal techniques to the problem of active vehicle suspensions in the presence of actuator time delays. Zhan et al .…”

mentioning

confidence: 99%

Special Issue on “Advances in Active Control of Sound and Vibration”: Editorial

Bai

Huang

Mace

et al. 2013

Asian Journal of Control

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Optimal Vibration Control for Vehicle Active Suspension Discrete‐Time Systems with Actuator Time Delay

Cited by 37 publications

References 21 publications

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Approximation Optimal Vibration for Networked Nonlinear Vehicle Active Suspension with Actuator Time Delay

Special Issue on “Advances in Active Control of Sound and Vibration”: Editorial

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Optimal Vibration Control for Vehicle Active Suspension Discrete‐Time Systems with Actuator Time Delay

Cited by 37 publications

References 21 publications

Robust distributedH∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Robust distributedH∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Approximation Optimal Vibration for Networked Nonlinear Vehicle Active Suspension with Actuator Time Delay

Special Issue on “Advances in Active Control of Sound and Vibration”: Editorial

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Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays