PI controller optimization for a heat exchanger through metaheuristic Bat Algorithm, Particle Swarm Optimization, Flower Pollination Algorithm and Cuckoo Search Algorithm

This paper presents the modeling and computer simulation of a control system for a shell and tube heat exchanger, using Bat Algorithms, Particle Swarm Optimization, Flower Pollination Algorithm and Cuckoo Search Algorithm. The temperature control logic is managed by a Proportional Integral-controller whose parameters were initially tuned using two methods of keeping the state of the art. To evaluate the performance of different methods of tuning, we compared the values of the transient of the response to step in eight mesh settings generated. It has also established a comparison between these two types of mesh using the performance indices proposed in the literature, with optimized system by Bat Algorithms got the best values of transient in relation to the Particle Swarm Optimization, Cuckoo Search Algorithm and Flower Pollination Algorithm. Performance indices FPA and PSO obtained better results.