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

Hussain, Amir and Abdullah, Rudwan and Yang, Erfu and Gurney, Kevin; Zhang, Huaguang and Hussain, Amir and Liu, Derong and Wang, Zhanshan, eds. (2012) An intelligent multiple-controller framework for the integrated control of autonomous vehicles. In: Advances in Brain Inspired Cognitive Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer Berlin/Heidelberg, CHN, pp. 92-101. ISBN 9783642315602

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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.

ORCID iDs

Hussain, Amir, Abdullah, Rudwan, Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950 and Gurney, Kevin; Zhang, Huaguang, Hussain, Amir, Liu, Derong and Wang, Zhanshan