A new adaptive hybrid controller for vibration control of a vehicle seat suspension featuring MR damper. (December 2017)

• Record Type: Journal Article
• Authors: Phu, Do Xuan; Choi, Sang-Min; Choi, Seung-Bok
• Is Part Of: Journal of vibration and control. Volume 23:Number 20(2017)
• Page Start: 3392
• Page End: 3413
• Publication Date: 2017-12
• Subjects: Magneto-rheological (MR) damper -- MR seat damper -- fuzzy neural – PI – sliding mode control -- hybrid control -- granular computing method -- granular clustering method -- seat suspension -- H- infinity technique; Vibration -- Periodicals; Damping (Mechanics) -- Periodicals; 620.3
• DOI: 10.1177/1077546316629597
• Languages: English
• ISSNs: 1077-5463

Abstract

This paper presents a new hybrid controller which is a combination of three control schemes: fuzzy neural control, PI control and sliding mode control. The interval type 2 fuzzy model featuring updated rules via online is used in this study and in order to support the fuzzy model, a granular clustering method is applied to find groups of data related to the initial fuzzy rule. Then the output for fuzzy model is used for the PI-sliding mode controller. The combination of PI and sliding mode controls is carried out by H-infinity technique method which is rely on the modified Riccati-like equation. After developing the mathematical model, the proposed controller is applied to vibration control of a vehicle seat suspension featuring magneto-rheological (MR) damper. In order to demonstrate the effectiveness of the proposed controller, two different excitations of bump and random signals are adopted and corresponding vibration control performances are evaluated. It is demonstrated through both simulation and experiment that the proposed controller can provide much better than vibration control performance compared with the conventional controllers showing more robust stability.