Fractional Order Controller for Web Transport System using Evolutionary Algorithms
The Web Transport System (WTS) is a complex process that contains series of roller arrangements to transfer the finished product (called web) for long distances. The tension acting on the web must be maintained within the acceptable limits to ensure material integrity and quality. However, the presence of nonlinearities, strong interactions and parametric variations in the WTS makes web tension control a challenging task. In this investigation, we propose a fractional order controller (FOC) for WTS process to maintain constant web tension. We utilize the additional degrees of freedom offered by FOC to tackle the nonlinearities and parametric variations in WTS. To tune the FOC parameters, we employ three evolutionary algorithms namely, Real Coded Genetic Algorithm (RGA), Bacterial Foraging Particle Swarm Optimization (BF-PSO) and Biogeographic Based Optimization (BBO). We perform simulation studies to analyze the FOC performance, and our results shows that the FOC tuned by BBO algorithm performs better than RGA and BF-PSO algorithms with improvement in material quality up to 26.3% and reduction in the material wastage up to 59.6%.