Akademik Veri Yönetim Sistemi
7th International Artificial Intelligence and Data Processing Symposium, Malatya, Türkiye, 7 - 08 Eylül 2023, ss.104-114
For crude oil operations, tank-level
monitoring and management are essential. Integrating soft control methods such
as fuzzy proportional-integral-derivative (FPID) into the management of these
operations can serve purposes such as increasing efficiency, reducing energy
consumption, reducing security risks, and improving product quality. The paper
presents the level control of a crude oil tank system using the FPID
controller. The mathematical model of the system is derived with the help of
flow, electrical and mechanical subcomponents. Takagi-Sugeno fuzzy inference
method and a 5x5 symmetrical rule base are both employed to construct the FPID
controller. The inputs of the fuzzy controller are determined as the tracking
error and the derivative of the tracking error and are expressed with
triangular membership functions. The proportional-integral-derivative (PID)
parameters of the controller are tuned through the genetic algorithm (GA). The
performance of the proposed FPID controller is compared with a conventional PID
controller whose parameters are also tuned with GA, in the simulation
environment in terms of certain performance metrics. Based on the simulation
results, the proposed FPID controller was better in all performance metrics
when dealing with single amplitude step input (up to 62.30%), multiple
amplitude step input (up to 7.29%), and multiple amplitude step input with disturbance
(up to 3.36%). The lower values of FPID in comparison to PID across all error
criteria indicate the higher robustness of the proposed controller.