Statistical control method based on optimal control theory with state observer for active suspension system
Konferenz: MEMAT 2022 - 2nd International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology
07.01.2022 - 09.01.2022 in Guilin, China
Tagungsband: MEMAT 2022
Seiten: 4Sprache: EnglischTyp: PDF
Autoren:
Wu, Jianwei (School of Mechanical Engineering, Southeast University, Nanjing, China & School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, China)
Jiang, Qiubo; Fu, Qidi; Sun, Beibei (School of Mechanical Engineering, Southeast University, Nanjing, China)
Inhalt:
This paper proposes the statistical control method based on linear quadratic regulation (LQR) for active suspension system, to improve the actuator’ life and reduce the influence of using state observer. Statistic control law with the luenberger observer based on LQR is derived by considering the statistical length and the bandwidth of the actuator. The control law is calculated by the statistical value of the input and output combining with the bandwidth of the actuator, not by the realtime state at any time, which reduces the influence of active suspension system from the state observer, noise and uncertianty. Simulation results demonstrates the effectiveness of the proposed control method under the minimum performance degradation, achieving an improvement in the energy input and actuator life, and also reducing the influence of using state observer. This statistical control provides a effective method for reducing the uncertainties from the real suspension system.