Adaptive control of a nonlinear suspension with time-delay compensation

Yao, Jun; Zhang, Jin Qiu; Zhao, Ming; Li, Xin

doi:10.21595/jve.2019.20077

Cited by 5 publications

(4 citation statements)

References 30 publications

(29 reference statements)

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“…There is a vast amount of literature showing the occurrence of such undesired resonances. 30–33 Therefore, a novel MIMO fuzzy logic controller is designed in this study as reported above. Figure 11 proves that the fuzzy MBAC shows a significant achievement in reduction of the magnitudes throughout the frequency responses with no undesired resonances.…”

Section: Results and Verification Of Controller Actionmentioning

confidence: 99%

Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator

Ozbek

Özgüney

Burkan

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article aims to improve the ride comfort of a vehicle keeping a satisfactory without road-holding performance by a novel adaptive control method that is insensitive to unknown system dynamics, model parameter changes, external disturbances and without any loss in suspension working space. With this purpose in mind, a new fuzzy integrated model-based adaptive control law for vehicle suspension systems is proposed in this study to improve the ride comfort and to ensure the robustness of system towards unknown model parameters and external disturbances. First, a model-based adaptive control law, which has the robust characteristics is presented. Afterwards, a multi-input multi-output fuzzy logic controller is designed to determine the controller gains dynamically. The stability of controller is ensured by Lyapunov Theory to achieve uniform boundedness error convergence. A 4 degree-of-freedom half-car model with active suspension system is used in this study to assess the performance of the controller. The results are compared among passive, model-based adaptive control law-controlled and novel fuzzy model-based adaptive control law-controlled systems. It has been concluded that fuzzy model-based adaptive control law further attenuates linear and angular motions of the vehicle increasing the ride comfort. The robustness is also verified for vehicle components having different possible parameter values. It is noteworthy that suspension working length returns to its initial position. Thus, the vehicle ride comfort is improved with no suspension working space loss. Finally, the economic feasibility of controllers has been checked in terms of energy consumption.

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Section: Results and Verification Of Controller Actionmentioning

confidence: 99%

Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator

Ozbek

Özgüney

Burkan

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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show abstract

“…Since the same control rate gain matrix is coupled to two different Lyapunov matrices X 1 and X 2 , the feedback gain cannot be directly calculated by inequalities (19)(20)(21)(22).…”

Section: Taylor Series-h 2 /H ∞ Control Strategymentioning

confidence: 99%

“…Recently, the robust control theorem has been widely applied to overcome the active suspension performance degradation caused by the time delay. Bououden et al [19] designed a robust model predictive control based on the Lyapunov–Krasovskii functional method for active suspension systems with time‐varying delays and input constraints, and the state feedback control law was calculated by solving an optimization problem using linear matrix inequality (LMI) terms. In addition, Sun et al [20] studied a finite frequency controller for an active suspension system actuator with an input delay.…”

Section: Introductionmentioning

confidence: 99%

“…Precision control is one of the core problems of the MR damper. To manage trade-offs among different control objectives, various control methods have been applied to control the semi-active suspension system such as optimal control [7,8], adaptive control [9], proportion integral derivative (PID) control [10], sliding mode control [11,12], and robust H 2 /H ∞ control [13,14]. Especially, the robust H 2 /H ∞ control approaches have been extensively reported, because these control approaches can not only improve suspension's ride comfort, but also restrain its safety performance constraints within a certain range.…”

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confidence: 99%

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Time delay compensation control using a Taylor series compound robust scheme for a semi‐active suspension with magneto rheological damper

Wang

Ren³

et al. 2021

Asian Journal of Control

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Time delay significantly degrades the control performances of semi‐active magneto rheological damper. However, the robust control approaches combined with the Taylor series are difficult to perform time delay compensation because it has strict application conditions. In this study, two Taylor series compound robust control schemes are presented to address the robust control and time delay compensation problems for the semi‐active magneto rheological damper with time delay. The formulation of a quarter vehicle model with a magneto rheological damper is described by a hyperbolic tangent model. Given the mechanical characteristics, an experimental test was conducted to fit the hyperbolic tangent model parameters. As a prototype, the Taylor series‐H2/H∞ control approach is proposed through establishing a first‐order Taylor series‐delay equation in augmented state equation and using the H2/H∞ norms to constrain the predictive control force. Moreover, the Taylor series‐H2/H2 controller is proposed to reduce the conservatism and suppress the predictive control force amplification. Simulation results corroborate the efficacy of both control strategies. Specifically, compared with the Taylor series‐H2/H∞ control, the Taylor series‐H2/H2 control can obtain a better control effect for time delay compensation.

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A semi-active suspension using a magnetorheological damper with nonlinear negative-stiffness component

Yang

Ning

Sun

et al. 2021

Mechanical Systems and Signal Processing

126

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Adaptive control of a nonlinear suspension with time-delay compensation

Cited by 5 publications

References 30 publications

Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator

Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator

Time delay compensation control using a Taylor series compound robust scheme for a semi‐active suspension with magneto rheological damper

A semi-active suspension using a magnetorheological damper with nonlinear negative-stiffness component

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