An introduction to genetic algorithms
An introduction to genetic algorithms
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Artificial Intelligence Review
Proceedings of the conference on Design, automation and test in Europe
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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This paper presents a VHDL-AMS based genetic optimization methodology suitable for performance improvement of hardware systems in automotive applications. Models of such systems are mixed-signal (analog and digital) in which the analog parts cover mixed physical domains. A case study applying this novel method to the fuzzy logic controller (FLC) optimization in an automotive active suspension system (AASS) has been investigated. A new type of fuzzy logic membership functions with variable geometrical shapes has been proposed and optimized. In this optimization technique, VHDL-AMS is used not only for the modeling and simulation of the FLC and its underlying AASS but also for the implementation of a parallel genetic algorithm (GA). This has resulted in an integrated performance optimization system wholly implemented in the hardware description language (HDL). Results show that the proposed FLC has superior performance to that of existing FLCs that use fixed-shape membership functions.