Genetic optimization of fuzzy fractional PD+I controllers

- Development of an optimal fuzzy fractional PD+I controller tuned by a GA.
- Performance analysis of several plant models representing industrial processes.
- Study of actuator saturation element and its influence in the control system performance.
- Study of different discretization schemes and their influence in the control system performance.

Fractional order calculus is a powerful emerging mathematical tool in science and engineering. There is currently an increasing interest in generalizing classical control theories and developing novel control strategies. The genetic algorithms (GA) are a stochastic search and optimization methods based on the reproduction processes found in biological systems, used for solving engineering problems. In the context of process control, the fuzzy logic usually means variables that are described by imprecise terms, and represented by quantities that are qualitative and vague. In this article we consider the development of an optimal fuzzy fractional PD+I controller in which the parameters are tuned by a GA. The performance of the proposed fuzzy fractional control is illustrated through some application examples.