Automatic design of nonlinear controllers by means of coevolutive algorithms application to an inverted pendulum

This paper focuses on the development of a tool to design nonlinear controllers automatically. This is done by means of an automatic stochastic search: a coevolutive algorithm, inspired by the competitive and symbiotic relationships between certain species in the Nature that evolve in parallel. The algorithm developed is used to look for a law that enable control of a classic system: the inverted pendulum. One of the two species that coevolve is made up of a set of control laws (each of them is a solution). The other one consist of initial conditions (that is a population of problems). The search space of the problem comprises all the possible solutions to it. The populations of the two species that evolve are processed by two different kinds of evolutive algorithms, a genetic algorithm and an algorithm that implements the Genetic Programming paradigm.