DESIGNING A NEURO-FUZZY CONTROLLER FOR A VEHICLE SUSPENSION SYSTEM, USING FEEDBACK ERROR LEARNING

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SADATI S.H.; ALIARI SHOUREHDELI M.; DAVARI EDALAT PANAH ALI

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Journal Paper

Paper Information

Journal: Journal of Aerospace Mechanics Year:2008 | Volume:4 | Issue:3 (13) Page(s): 45-57

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Title

DESIGNING A NEURO-FUZZY CONTROLLER FOR A VEHICLE SUSPENSION SYSTEM, USING FEEDBACK ERROR LEARNING

Author(s)

SADATI S.H. | ALIARI SHOUREHDELI M. | DAVARI EDALAT PANAH ALI | Issue Writer Certificate

Keywords

NEURO-FUZZYQ3

ACTIVE SUSPENSIONQ3

NEURAL NETWORKQ2

FELQ3

Abstract

In the present research, a non-linear controller is designed for the control of an ACTIVE SUSPENSION system for a half-model vehicle, using a Fuzzy NEURAL NETWORK (FNN) along with Feedback error learning. The purpose in a vehicle suspension system is reduction of transmittance of vibrational effects from the road to the vehicle chassis, hence providing ride comfort. This requires a minimum reduction in road contact along rough roads. In addition, the role of the suspension system in vehicle control along a curved route and in accelerating and braking is quite evident. To accomplish this, one can first design a PD controller for the suspension system, using a classic control method and use it to train a fuzzy controller. This controller can be trained using the PD controller output error on an online manner. Once trained, the PD controller is removed from the control loop and the NEURO-FUZZY controller takes on. In case of a change in the parameters of the system under control, the PD controller enters the control loop again and the NEURAL NETWORK gets trained again for the new condition. Important characteristics of the proposed controller are that no mathematical model is needed for the system components, such as the non-linear actuator, spring, or shock absorber, and that no system Jacobian is needed. The performance of the proposed FNN controller is compared with that of the PD controller through simulations. The results show that the proposed controller is indeed capable of meeting the stated control requirements.

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APA: Copy

SADATI, S.H., ALIARI SHOUREHDELI, M., & DAVARI EDALAT PANAH, ALI. (2008). DESIGNING A NEURO-FUZZY CONTROLLER FOR A VEHICLE SUSPENSION SYSTEM, USING FEEDBACK ERROR LEARNING. AEROSPACE MECHANICS JOURNAL, 4(3 (13)), 45-57. SID. https://sid.ir/paper/102096/en

Vancouver: Copy

SADATI S.H., ALIARI SHOUREHDELI M., DAVARI EDALAT PANAH ALI. DESIGNING A NEURO-FUZZY CONTROLLER FOR A VEHICLE SUSPENSION SYSTEM, USING FEEDBACK ERROR LEARNING. AEROSPACE MECHANICS JOURNAL[Internet]. 2008;4(3 (13)):45-57. Available from: https://sid.ir/paper/102096/en

IEEE: Copy

S.H. SADATI, M. ALIARI SHOUREHDELI, and ALI DAVARI EDALAT PANAH, “DESIGNING A NEURO-FUZZY CONTROLLER FOR A VEHICLE SUSPENSION SYSTEM, USING FEEDBACK ERROR LEARNING,” AEROSPACE MECHANICS JOURNAL, vol. 4, no. 3 (13), pp. 45–57, 2008, [Online]. Available: https://sid.ir/paper/102096/en

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