Microcontroller implementation of a multi objective genetic algorithm for real-time intelligent control

Abstract

This paper presents an approach to merge three elements that are usually not thought to be combined in one application: evolutionary computing running on reasonably priced microcontrollers (μC) for real-time fast control systems. A Multi Objective Genetic Algorithm (MOGA) is implemented on a 180MHz μC.A fourth element, a Neural Network (NN) for supporting the evaluation function by predicting the response of the controlled system, is also implemented. Computational performance and the influence of a variety of factors are discussed. The results open a whole new spectrum of applications with great potential to benefit from multivariable and multiobjective intelligent control methods in which the hybridization of different soft-computing techniques could be present. The main contribution of this paper is to prove that advanced soft-computing techniques are a feasible solution to be implemented on reasonably priced μC -based embedded platforms.