Proportional-integral-derivative control algorithm with delay compensation for steer-by-wire under network controlled system
Controller Area Network (CAN) is a popular network commonly used in the automotive industry which is an advanced serial bus system designed for real-time control system. This thesis addresses the modelling and controller design for Steer-by-Wire (SbW) system under the influence of a network controll...
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/78776/1/MohdSazlanZainalMFKE2015.pdf http://eprints.utm.my/id/eprint/78776/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106112 |
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| Summary: | Controller Area Network (CAN) is a popular network commonly used in the automotive industry which is an advanced serial bus system designed for real-time control system. This thesis addresses the modelling and controller design for Steer-by-Wire (SbW) system under the influence of a network controlled system. The analysis of the control performance of the SbW system under several CAN configuration setting is discussed in detail. The mathematical model of the SbW system is adopted from previous research works using both steering rack dynamic and the vehicle system dynamic. Proportional-Integral-Derivative (PID) controller that can compensate delay is designed to achieve the desired control performance of the SbW system. The analysis of the control performance is solely based on the simulation conducted in the Matlab/Simulink software environment with Truetime toolbox to simulate the real time performance of the SbW system. The simulation is performed based on nine different cases in the event of several difference in the CAN network properties such as the network speed, sampling periods, scheduling techniques, rate of data losses, interruption by higher priority data and clock drift to evaluate the control performance of the SbW system. The result is found that the SbW system control performance deteriorates by the selection of low network speed, sensor’s sampling periods and the rate of data losses. |
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