Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16514
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Yang, Erfu
Hussain, Amir
Gurney, Kevin
Contact Email: amir.hussain@stir.ac.uk
Title: Neurobiologically-inspired soft switching control of autonomous vehicles
Editors: Zhang, H
Hussain, A
Liu, D
Wang, Z
Citation: Yang E, Hussain A & Gurney K (2012) Neurobiologically-inspired soft switching control of autonomous vehicles. In: Zhang H, Hussain A, Liu D, Wang Z (ed.). Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings. Lecture Notes in Computer Science, 7366, Berlin Heidelberg: Springer, pp. 82-91.
Issue Date: 2012
Series/Report no.: Lecture Notes in Computer Science, 7366
Conference Name: 5th International Conference, BICS 2012
Conference Dates: 2012-07-11T00:00:00Z
Conference Location: Shenyang, China
Abstract: A novel soft switching control approach is presented in this paper for autonomous vehicles by using a new functional model for Basal Ganglia (BG). In the proposed approach, a family of fundamental controllers is treated as each of a set of basic controllers are thought of as an ‘action' which may be selected by the BG in a soft switching regime for real-time control of autonomous vehicle systems. Three controllers, i.e., conventional Proportional-Integral-Derivative (PID) controller, a PID structure-based pole-zero placement controller, and a pole only placement controller are used in this paper to support the proposed soft switching control strategy. To demonstrate the effectiveness of the proposed soft switching approach for nonlinear autonomous vehicle control (AVC), the throttle, brake and steering subsystems are focused on in this paper because they are three key subsystems in the whole AVC system. Simulation results are provided to illustrate the performance and effectiveness of the proposed soft switching control approach by applying it to the abovementioned subsystems.
Type: Part of book or chapter of book
Status: Book Chapter: publisher version
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
URI: http://hdl.handle.net/1893/16514
URL: http://link.springer.com/chapter/10.1007/978-3-642-31561-9_9#
Affiliation: Computing Science - CSM Dept
Computing Science - CSM Dept
University of Sheffield

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