An intelligent multiple-controller framework for the integrated control of autonomous vehicles

Hussain, A.; Abdullah, R.; Yang, E.; Gurney, K.

Abstract

This paper presents an intelligent multiple-controller framework for the integrated control of throttle, brake and steering subsystems of realistic validated nonlinear autonomous vehicles. In the developed multiple-controller framework, a fuzzy logic-based switching and tuning supervisor operates at the highest level of the system and makes a switching decision on the basis of the required performance measure, between an arbitrary number of adaptive controllers: in the current case, between a conventional Proportional-Integral-Derivative (PID) controller and a PID structure-based pole-zero placement controller. The fuzzy supervisor is also able to adaptively tune the parameters of the multiple controllers. Sample simulation results using a realistic autonomous vehicle model demonstrate the ability of the intelligent controller to both simultaneously track the desired throttle, braking force, and steering changes, whilst penalising excessive control actions - with significant potential implications for both fuel and emission economy. We conclude by demonstrating how this work has laid the foundation for ongoing neuro-biologically motivated algorithmic development of a more cognitively inspired multiple-controller framework.

Citation

Hussain, A., Abdullah, R., Yang, E., & Gurney, K. (2012, July). An intelligent multiple-controller framework for the integrated control of autonomous vehicles. Presented at 5th International Conference, BICS 2012, Shenyang, China

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 5th International Conference, BICS 2012
• Start Date: Jul 11, 2012
• End Date: Jul 14, 2012
• Publication Date: 2012
• Deposit Date: Oct 11, 2019
• Publisher: Springer
• Pages: 92-101
• Series Title: Lecture Notes in Computer Science
• Series Number: 7366
• Book Title: Advances in Brain Inspired Cognitive Systems
• ISBN: 978-3-642-31560-2
• DOI: https://doi.org/10.1007/978-3-642-31561-9_10
• Keywords: Autonomous vehicle control, PID controller, pole-zero placement controller, fuzzy logic switching and tuning
• Public URL: http://researchrepository.napier.ac.uk/Output/1793188