A Basal Ganglia Inspired Soft Switching Approach to the Motion Control of a Car-Like Autonomous Vehicle
- 2k Downloads
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.
KeywordsBrain-inspired computing basal ganglia cognitive computation autonomous vehicles motion control soft switching multiple controller systems action selection fuzzy logic
Unable to display preview. Download preview PDF.
- 6.Gurney, K., Hussain, A., Chambers, J., Abdullah, R.: Controlled and automatic processing in animals and machines with application to autonomous vehicle control. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009, Part I. LNCS, vol. 5768, pp. 198–207. Springer, Heidelberg (2009)CrossRefGoogle Scholar
- 8.Yang, E., Gu, D., Mita, T., Huo, H.: Nonlinear tracking control of a car-like mobile robot via dynamic feedback linearization. In: Proc. Control 2004, Bath, UK (2004)Google Scholar
- 9.Sastry, S.: Nonlinear Systems-Analysis, Stability, and Control. Springer-Verlag New York, Inc. (1999)Google Scholar