Submarine sliding mode controller optimisation using genetic algorithms

A nonlinear control application of genetic algorithm (GA) optimisation techniques is studied in this paper. The theory of the application is presented from its basis in Darwinian evolution to the development of the form of optimisation algorithm used in the application. This involves sliding mode (SM) controllers for the diving and heading manoeuvres of a linear submarine model. The GA optimised results are compared with hand-tuned results in terms of performance and acquisition time. Post-optimisation analysis of the GA results has shown that in order to obtain good performance the GA solution involves controllers which operate in a specific region. The selection of this region effectively changes the structure of the controllers.