Optimal tuning procedure for FOPID controller of integrated industrial processes with deadtime

Industrial processes such as batch distillation columns, supply chain, level control etc. integrate dead times in the wake of the transportation times associated with energy, mass and information. The dead time, the cause for the rise in loop variability, also results from the process time and accumulation of time lags. These delays make the system control poor in its asymptotic stability, i.e. its lack of self-regulating savvy. The haste of the controller’s reaction to disturbances and congruence with the design specifications are largely influenced by the dead time; hence it exhorts a heed. This article is aimed at answering the following question: “How can a fractional order proportional integral derivative controller (FOPIDC) be tuned to become a perfect dead time compensator apposite to the dead time integrated industrial process?” The traditional feedback controllers and their tuning methods do not offer adequate resiliency for the controller to combat out the dead time. The whale optimization algorithm (WOA), which is a nascent (2016 developed) swarm-based meta-heuristic algorithm impersonating the hunting maneuver of a humpback whale, is employed in this paper for tuning the FOPIDC. A comprehensive study is performed and the design is corroborated in the MATLAB/Simulink platform using the FOMCON toolbox. The triumph of the WOA tuning is demonstrated through the critical result comparison of WOA tuning with Bat and particle swarm optimization (PSO) algorithm-based tuning methods. Bode plot based stability analysis and the time domain specification based transient analysis are the main study methodologies used.

Abstract licence: CC BY

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