Impact of fractional order methods on optimized tilt control for rail vehicles

Hassan, Fazilah and Zolotas, Argyrios (2017) Impact of fractional order methods on optimized tilt control for rail vehicles. Fractional Calculus & Applied Analysis, 20 (3). ISSN 1311-0454

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Item Type:Article
Item Status:Live Archive

Abstract

Advances in the use of fractional order calculus in control theory in-
creasingly make their way into control applications such as in the process
industry, electrical machines, mechatronics/robotics, albeit at a slower rate
into control applications in automotive and railway systems. We present
work on advances in high-speed rail vehicle tilt control design enabled by
use of fractional order methods. Analytical problems in rail tilt control still
exist especially on simplified tilt using non-precedent sensor information
(rather than use of the more complex precedence (or preview) schemes).
Challenges arise due to suspension dynamic interactions (due to strong
coupling between roll and lateral dynamic modes) and the sensor measure-
ment. We explore optimized PID-based non-precedent tilt control via both
direct fractional-order PID design and via fractional-order based loop shap-
ing that reduces effect of lags in the design model. The impact of fractional
order design methods on tilt performance (track curve following vs ride
quality) trade off is particularly emphasized. Simulation results illustrate
superior benefit by utilizing fractional order-based tilt control design.

Keywords:Fractional Calculus, Fractional Order Control, Optimization, Tilt Control, railway vehicles, Active suspensions, Non-minimum phase zeros
Subjects:H Engineering > H660 Control Systems
H Engineering > H100 General Engineering
H Engineering > H332 Rail Vehicle Engineering
G Mathematical and Computer Sciences > G530 Systems Analysis and Design
J Technologies > J990 Technologies not elsewhere classified
G Mathematical and Computer Sciences > G120 Applied Mathematics
Divisions:College of Science > School of Engineering
ID Code:27565
Deposited On:24 May 2017 12:14

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