Open Access
Issue |
ITM Web Conf.
Volume 40, 2021
International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|
|
---|---|---|
Article Number | 01001 | |
Number of page(s) | 9 | |
Section | Automation | |
DOI | https://doi.org/10.1051/itmconf/20214001001 | |
Published online | 09 August 2021 |
- J. Wang and L. Sun, “Design of semi-active air suspension system based on backstepping sliding mode control,” 2017 Chinese Automation Congress (CAC), 2017, pp. 4378–4382, doi: 10.1109/CAC.2017.8243550. [Google Scholar]
- E. Enders, P. Karle, G. Bonelli, D. Killian and G. Burkhard, “Modal Vertical Vehicle Dynamics Control for Semi-Active and Active Suspension Systems,” 2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), 2020, pp. 1–9, doi: 10.1109/EVER48776.2020.9242985. [Google Scholar]
- J. Wu, H. Zhou, Z. Liu and M. Gu, “Ride Comfort Optimization via Speed Planning and Preview Semi-Active Suspension Control for Autonomous Vehicles on Uneven Roads,” in IEEE Transactions on Vehicular Technology, vol. 69, no. 8, pp. 8343–8355, Aug.2020, doi: 10.1109/TVT.2020.2996681. [Google Scholar]
- Gowda, Dr.Dankan and Chakrasali, Sadashiva. (2014). Comparative Analysis of Passive and Semi-Active Suspension System for Quarter Car Model using PID Controller. [Google Scholar]
- Qazi, Abroon & Khan, Dr. Afzal & Khan, Muhammad & Noor, Sahar. (2013). A Parametric Study on Performance of Semi-active Suspension System with Variable Damping Coefficient Limit. AASRI Procedia. 4. 154–159. 10.1016/j.aasri.2013.10.024. [Google Scholar]
- Karthik Murali Madhavan Rathai. Experimental Implementation of Model Predictive Control Scheme for Control of Semi-active Suspension System. ScienceDirect, 2019. [Google Scholar]
- Wen, Jinyu & Liu, Ju & Long, Yao & Yao, Wei. (2016). Solution to short-term frequency response of wind farms by using energy storage systems. IET Renewable Power Generation.10. 669–678. 10.1049/iet-rpg.2015.0164 [Google Scholar]
- Abroon Jamal Qazi Afzal Khan, M. Tahir Khan, Sahar Noor. A Parametric Study on Performance of Semi-Active SuspensionSystem with Variable Damping Coefficient Limit,2014. [Google Scholar]
- Kazima, Sosthene and Josee, Musabyimana and Hui, Xiong. (2018). Fuzzy Logic Controller for Semi Active Suspension Based on MagnetoRheological Damper. International Journal of Automotive Engineering and Technologies. Volume 7. [Google Scholar]
- Hung, N.C., Nhung, N.T.B., Vu, L.T.Y., Khai, V.Q., Son, T.A., Thanh, T.Q., 2020. Apply a Fuzzy Algorithm to Control an Active Suspension in a Quarter Car by Matlab’s Simulink. AMM 902, 23–32. https://doi.org/10.4028/www.scientific.net/amm.902.23 [Google Scholar]
- Abellan-Nebot, Jose. (2010). A review of artificial intelligent approaches applied to part accuracy prediction. International Journal of Machining and Machinability of Materials. 8. [Google Scholar]
- Yao, G. Z. et al. “MR damper and its application for semi-active control of vehicle suspension system.” Mechatronics 12 (2002): 963–973. [Google Scholar]
- Pang, Hui Liu, Fan Xu, Zeren. (2018). Variable universe fuzzy control for vehicle semi-active suspension system with MR damper combining fuzzy neural network and particle swarm optimization. Neurocomputing. 306. 10.1016/j.neucom.2018.04.055. [Google Scholar]
- Durieux, Olivier Abramov, Sergey Mannan, Samjid. (2009). Semi-active suspension system simulation using Simulink. International Journal of Engineering Systems Modelling and Simulation. 1. 101–114. 10.1504/IJESMS.2009.027573. [Google Scholar]
- Juan C. Tudon-Martınez, Rubén Morales-Menéndez, Ricardo Ramirez-Mendoza, Olivier Sename, Luc Dugard. A Comparison between a Model-free and Model-based Controller of an Automotive Semi-active Suspension System: Independent Wheelstations. IFAC Joint conference SSSC - 5th Symposium on System Structure and Control, Feb 2013, Grenoble, France. pp.869–874, [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.