Optimal sliding mode control of semiactive suspension system
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
Key Words: Semiactive Suspension, Lqr, Sliding Mode Kontrol Whole body vibration is an important problem facing operators of heavy vehicles. Research has shown that drivers exposed to low frequency whole body vibration can experience temporary and even permanent injuries. One solution to this problem is to develop a semi active seat capable of canceling the vibrations felt by the driver. Several passive, semiactive, active, and fully active seats have been designed and built to address this problem. Controllers have been developed to optimize the seat performance. Vibration cancellation seating systems seem to be a promising and practical way to reduce the effects of whole body vibration. The semi active seat suspension system utilizes a spring and MR damper. Controllers were developed to control the acceleration of the seat, as well as cancel unwanted vibration. To simulation the performance of the Semi Active seat suspension system, the system identification of the seat was undertaken using open loop forcing functions. The seat was evaluated in each degree of freedom to understand the potential of the seat to cancel harmful vibration and acceleration.
Author
Melih Göksel
Institution
How to Cite
Melih Göksel (Master Thesis). Optimal sliding mode control of semiactive suspension system, 2007, Sakarya University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Sakarya University
- Turkey according to the records of the House of Commons (1918-1922)(2011)
- Ömer Öngüt, his views and community through publications(2025)
- Mawlana Yaqub-i Charkhi And His tafsir(2024)
- Research of teachers' attitudes and self-efficacy perceptions towards distance education application(2024)
- Tiles in architect Vedat Tek's Istanbul buildings(2024)
- Financial performance evaluation and the relationship between stock returns: Hesitant Fuzzy AHP based approach(2020)
