On-line multiobjective automatic control system generation by evolutionary algorithms

Evolutionary algorithms are applied to the on-line generation of servo-motor control systems. In this paper, the evolving population of controllers is evaluated at run-time via hardware in the loop, rather than on a simulated model. Disturbances are also introduced at run-time in order to produce robust performance. Multiobjeciive optimisation of both PI and fuzzy logic controllers is considered. Finally an on-line implementation of genetic programming is presented based around the Simulink standard blockset. The on-line designed controllers are shown to be robust to both system noise and external disturbances while still demonstrating excellent steady-state and dynamic characteristics.