Genetic design of robust PID controllers to deal with prescribed plant uncertainties through a process of competitive co-evolution

Artificial co-evolutionary techniques are proposed in a new and novel paradigm to solve the problem of designing a robust fixed PID controller for a plant with prescribed plant uncertainties. The co-evolutionary scheme used, involves generating two separate populations, one representing the controller and the other the plant. Two separate cost functions are then used in the co-evolutionary scheme to reflect the different goals of the two populations. The two populations are then co-evolved such that the population of plants, with the prescribed uncertainties, contains the set of difficult plants to control and a population of controllers emerges, which can control all these difficult plants effectively. The resulting paradigm not only results in a robust controller design but also produces a set of worst case plants. This co-evolutionary approach is illustrated through co-evolving a PID controller for a linear plant which has a set of prescribed uncertainties