Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network. Issue 17 (November 2020)

• Record Type: Journal Article
• Authors: Phu, Do Xuan; Mien, Van
• Is Part Of: Journal of the Franklin Institute. Volume 357:Issue 17(2020)
• Page Start: 12281
• Page End: 12307
• Publication Date: 2020-11
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2020.09.011
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This study proposes a novel adaptive control method to deal with the dead-zone and time delay issues in actuators of vibration control systems. The controller is formulated based on a type-2 fuzzy neural network integrating with a new modification of Riccati-like equation. The developed new type Riccati-like equation is significant as it reduces energy consumption of control inputs to minimum. Two approaches are suggested to improve performance of the system using the basic elements of Riccati equation. In addition, a fuzzy neural network is applied to approximate the unmodeled dynamics and a sliding mode controller is developed to enhance the robustness of the system against uncertainties and disturbances. After proving the stability of the proposed controller via Lyapunov criterion, the effectiveness of the proposed approach is validated based on computer simulation for vibration control of a vehicle seat suspension. It is demonstrated that the unwanted vibrations due to external excitations are well controlled despite of the presence of dead-zone and time delay in actuators. Furthermore, when comparing with other two state-of-the-art robust controllers [23, 33 ], the proposed controller provides better vibration suppression capacity and requires less energy consumption.