2018
DOI: 10.1049/iet-cta.2017.0970
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Robust control of an active suspension system with actuator time delay by predictor feedback

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Cited by 35 publications
(15 citation statements)
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References 39 publications
(87 reference statements)
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“…In physical and practical systems, signals to control systems are not known but are random and stochastic in nature [35]. Terefore, it seems that the behavior of the controller in the presence of a stochastic disturbance is more like the real world than the constant disturbance.…”
Section: Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…In physical and practical systems, signals to control systems are not known but are random and stochastic in nature [35]. Terefore, it seems that the behavior of the controller in the presence of a stochastic disturbance is more like the real world than the constant disturbance.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Te H ∞ control method based on the predictor that has been presented in [35] for an LTI system in the presence of input delay and external disturbance is briefy recalled in this section.…”
Section: Presentation and Formulation Of The Methodsmentioning
confidence: 99%
“…In a control system with sensing delay, the controller may only have past information about state variables of the plant (sensing delay) and in a control system with actuation delay, the updated control signal may never reach the plant promptly (actuation delay). One of the most common stabilization methods in this context is based on using the family of predictor feedback controllers, 3,5,8,9,[12][13][14][15][16] due to their ability in prediction of the state variables of dynamical systems. Due to the implementation difficulty of predictor feedback, 12,13 it has been simplified to the truncated predictor one.…”
Section: Introductionmentioning
confidence: 99%
“…One of the most common stabilization methods in this context is based on using the family of predictor feedback controllers, 3,5,8,9,[12][13][14][15][16] due to their ability in prediction of the state variables of dynamical systems. Due to the implementation difficulty of predictor feedback, 12,13 it has been simplified to the truncated predictor one. Yoon and Lin 14 have designed a truncated predictor state feedback controller for stabilization of a linear system with the known delay value.…”
Section: Introductionmentioning
confidence: 99%
“…An actuator fault compensation scheme is proposed, which can achieve arbitrarily small tracking errors in the presence of nonlinear actuators with random faults [5]. And there are more and more control strategies for active suspension, such as H∞ control [4,[8][9][10][11], optimal control [12][13][14][15], neural network control [16][17][18][19], LQG control [20,21], predictive control [22], and sliding mode control [14,23].…”
Section: Introductionmentioning
confidence: 99%