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Predictive Control Strategies Used to Solve Challenges Related to Modern Railway Vehicles

Ngigi, R. W., Pislaru, Crinela, Ball, Andrew, Fengshou, Gu and Anyakwo, Arthur (2011) Predictive Control Strategies Used to Solve Challenges Related to Modern Railway Vehicles. In: 5th IET Conference on Railway Condition Monitoring and Non-Destructive Testing (RCM 2011), 29-30 November 2011, Derby Conference Centre, UK.

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This paper is an attempt to collate and critically appraise the recent advances in control strategies used to solve challenges
related to railway vehicles which present nonlinearities and uncertainties. These strategies concentrate on stability of solid
axle-wheelsets, guidance for wheelsets to provide the function of track following and curving to reduce all unnecessary creep forces and associated wear/noise. The focus is on active
primary and secondary suspensions, braking and traction subsystems.
This paper examines potential new and efficient
applications of modern predictive control methods, analysis tools and techniques which could be used in effective and
reliable condition monitoring systems allowing informed decision making on maintenance and renewals activities.

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Item Type: Conference or Workshop Item (Paper)
Additional Information: © IET
Uncontrolled Keywords: rail vehicle dynamics, active control, condition monitoring, predictive analysis techniques, intelligent sensing
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
Related URLs:
References: [1] A. H. Wickens. "Fundamentals of rail vehicle dynamics: guidance and stabilit", Taylor & Francis, (2003). [2] H. Selamat, R. Yusof, R. M. Goodall. “Self-Tuning Control For Active Steering Of A Railway Vehicle With Solid-Axle Wheelsets”, IET Control Theory & Applications, vol 2, no. 5, pp. 374-383, (2008). [3] R. M. Goodall, H. Li. “Solid Axle and Independently-Rotating Railway Wheelsets - A Control Engineering Assessment of Stability”, Vehicle System Dynamics,vol 33, pp. 57-67, (2000). [4] R. M. Goodall, W. Kortüm. “Mechatronic Developments For Railway Vehicles Of The Future”, Control Engineering Practice, volume 10, no. 8, pp. 887-898, (2002). [5] U. Viereck, T. Stützle, W. Rulka,, A. Stribersky.“Analysis Of The Braking Performance Of A Rail Vehicle Emphasizing Mechatronic Components”,Vehicle System Dynamics, vol 44, pp. 823-833,(2006). [6] R.M. Goodall, T.X. Mei. “Active Suspensions,” in Handbook of Railway Vehicle Dynamics, CRC Press, pp.327-357, (2006). [7] S. Bruni, R. Goodall, T. X. Mei, H. Tsunashima.“Control And Monitoring For Railway Vehicle Dynamics”, Vehicle System Dynamics, volume 45, pp.743-779, (2007). [8] R. M. Goodall, S. Bruni, T. X. Mei. “Concepts And Prospects For Actively Controlled Railway Running Gear”, Vehicle System Dynamics, volume 44, pp. 60-70,(2006). [9] J.H. Yu, T.X. Mei, D.A. Wilson. “Re-adhesion control based on wheelset dynamics in railway traction system,”UKACC Int Control Conference on Control,(2006). [10] T.X. Mei, J.H. Yu, D.A. Wilson. "A Mechatronic Approach For Effective Wheel Slip Control In Railway Traction", Journal of Rail and Rapid Transit, vol 223, pp. 295-304, (2009). [11] I. Hasegawa, S. Uchida, “Braking Systems,” Railway Technology Today 7, pp. 52-59, (1999). [12] S. J. Qin, T. A. Badgwell, “A Survey Of Industrial Model Predictive Control Technology”, Control Engineering Practice, volume 11, no. 7, pp. 733-764, (2003). [13] R. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Transactions of the ASME –Journal of Basic Engineering, no. 82, pp. 35-45, (1960). [14] Li, R. Goodall, P. Weston, C. Sengling, C. Goodman, C. Roberts, “Estimation Of Railway Vehicle Suspension Parameters For Condition Monitoring,” Control Engineering Practice, volume 15, no. 1, pp. 43-55, 2007. [15] C. Rao, J. Rawlings, “Constrained process monitoring: Moving-horizon approach,” AIChE Journal, volume 48, no. 1, pp. 97-109, (2002). [16] S. Hovl, J. T. Gravdahl, K. E. Willcox, “Explicit Model Predictive Control for Large-Scale Systems via Model Reduction.” AIAA Journal of Guidance, Control, and Dynamics, volume 31, pp. 918-926, (2008).
Depositing User: Crinela Pislaru
Date Deposited: 17 May 2012 14:31
Last Modified: 28 Aug 2021 20:51


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