Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16522
Appears in Collections:Computing Science and Mathematics Book Chapters and Sections
Title: A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle
Author(s): Yang, Erfu
Hussain, Amir
Gurney, Kevin
Contact Email: amir.hussain@stir.ac.uk
Editor(s): Liu, D
Alippi, C
Zhao, D
Hussain, A
Sponsor: The Royal Society of Edinburgh
Citation: Yang E, Hussain A & Gurney K (2013) A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In: Liu D, Alippi C, Zhao D & Hussain A (eds.) Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. Lecture Notes in Computer Sci, 7888. 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, Beijing, China, 09.06.2013-11.06.2013. Berlin Heidelberg: Springer, pp. 245-254. http://link.springer.com/chapter/10.1007/978-3-642-38786-9_28#; https://doi.org/10.1007/978-3-642-38786-9_28
Keywords: Brain-inspired computing
basal ganglia
cognitive computation
autonomous vehicles
motion control
soft switching
multiple controller systems
action selection
fuzzy logic
Issue Date: 2013
Date Deposited: 8-Aug-2013
Series/Report no.: Lecture Notes in Computer Sci, 7888
Abstract: This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.
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.
URL: http://link.springer.com/chapter/10.1007/978-3-642-38786-9_28#
DOI Link: 10.1007/978-3-642-38786-9_28
Licence URL(s): http://www.rioxx.net/licenses/under-embargo-all-rights-reserved

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