Hybrid variable structure-fuzzy control of a magnetorheological damper for a seat suspension

Stammers, Charles W; Stancioiu, Dan; Sireteanu, Tudor; Ghigliazza, R.

doi:10.1504/ijvas.2005.007036

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…Takagi-Sugeno fuzzy model [137] Fuzzy linear regression [9] Fuzzy preview control [138] Model reference adaptive fuzzy control [44] Neuro-fuzzy method [123] Hierarchical fuzzy integral [24] Fuzzy clustering [139] Type-II fuzzy system [140] Sliding mode control [141] Grey predictor [142] PI and PID control [91,143] Genetic algorithm [71,144] Optimization gradient method [145] Multi-objective optimization [108] Variable structure control [146] Reinforcement learning [94] Bayesian methods [147] in automotive engineering applications. The following positions can be especially mentioned in this context:…”

Section: Conventional Fuzzy Methods Methods / Tools Integrated With Fmentioning

confidence: 99%

A review of fuzzy methods in automotive engineering applications

Ivanov

2015

Eur. Transp. Res. Rev.

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Purpose The paper addresses evolution of fuzzy systems for core applications of automotive engineering. Methods The presented study is based on the analysis of bibliography dedicated to fuzzy sets and fuzzy control for ground vehicles. A special attention is given to fuzzy approaches used in the following domains of automotive engineering: vehicle dynamics control systems, driver and driving environment identification, ride comfort control, and energy management of electric vehicles. Results The bibliographical analysis, supplemented with statistics of relevant research publications, has allowed to allocate the most important fuzzy application cases for each domain. In particular, it concerns driver identification, humanmachine interface, recognition of road conditions, and controllers of vehicle chassis and powertrain systems. It is found out that fuzzy methods have the primary use most of all for tasks requiring identification and forecasting procedures, especially in conditions of limited informational space. Additional observation that can be also derived from the presented survey points to reasonable integration of fuzzy technique with other control engineering methods to improve the performance of automotive control systems. Conclusions In the aggregate the performed review indicates that fuzzy computing can be considered as a versatile tool for automotive engineering applications of different nature.

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Section: Conventional Fuzzy Methods Methods / Tools Integrated With Fmentioning

confidence: 99%

A review of fuzzy methods in automotive engineering applications

Ivanov

2015

Eur. Transp. Res. Rev.

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“…Two of the present authors and co-workers initially explored the use of controlled friction dampers in automotive applications [1,2] and have subsequently directed their research effort towards magnetorheological dampers (MRDs) [3,4] for vehicles and most recently for trucks. Details of MRD design and modelling and of the properties of magnetorheological fluids can be found in references [5] to [8].…”

Section: Introductionmentioning

confidence: 99%

Semi-active control of a passenger vehicle for improved ride and handling

Tsampardoukas

Stammers

2008

Proceedings of the Institution of Mechanical Engineers, Part D:

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A theoretical model is developed for the semi-active control of the suspension of a full passenger car using a variable-structure-type algorithm. Skyhook control and variants of balance control (cancelling or adding the dynamic spring forces) are applied via a magnetorheological damper at the front and rear wheels to improve the vehicle ride and handling. The magnetorheological damper is modelled via a Bouc—Wen approach. The semi-active vehicle response is compared with a passive response. The robustness of control is established by adding noise to the computed sensor inputs, and the loose-wire scenario is also considered. The results show that balance control is a robust algorithm. The magnitude of acceleration reduction (for the human body and head—neck complex) using semi-active control varies with the semi-active approach and vehicle speed (a simulated random road was assumed). At 30m/s the human body acceleration reduction was found to be 70 per cent with skyhook control and 40 per cent with balance control (cancelling the dynamic spring forces). The handling manoeuvres of the vehicle are presented utilizing BS ISO 3888-1 1999. The handling performance of the vehicle is significantly improved, when balance control by cancelling is applied on the rear dampers only. Using skyhook control and balance control by adding a spring force to the system it is not possible to improve the handling response of the vehicle.

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