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Sistem Kontrol Governor Menggunakan Pid Yang Dioptimasi Dengan Metode Cuckoo Search Algorithm (Csa)
Author(s) -
Mochamad Riduwan,
Fachrudin Hunaini,
Muh Mukhsim
Publication year - 2019
Publication title -
jeee-u (journal of electrical and electronic engineering-umsida)
Language(s) - English
Resource type - Journals
eISSN - 2540-8658
pISSN - 2460-9250
DOI - 10.21070/jeee-u.v3i1.2090
Subject(s) - pid controller , cuckoo search , control theory (sociology) , governor , control engineering , controller (irrigation) , generator (circuit theory) , engineering , dc motor , computer science , power (physics) , control (management) , algorithm , artificial intelligence , temperature control , particle swarm optimization , agronomy , physics , electrical engineering , quantum mechanics , biology , aerospace engineering
Indonesia has enormous potential for the Hydroelectric Power Plant (PLTA). Considering that PLTA is an environmentally friendly power plant, the components of this plant are worthy of further development. One of them is the development of the hydropower governoor control system. The PID controller is a control system that is often used in the control of the Governoor System in a hydropower plant because of its simple controller. At present hydro power plants still use the conventional method of PID control trial-error on average. For this method it is difficult to adjust parameters and it takes a long time and the accuracy of controls is not good. Therefore a smart method is needed to overcome this problem. In the past few years, researchers have used many intelligent methods (Artificial Intelligent) to determine the DC PID parameters. One of them is Cucckoo Search Algorithm (CSA) which is inspired by the behavior of cuckoo birds in placing their eggs. By using the CSA method, it is expected to provide a better system response than using the old system PID control (trial-error). The final goal of the PID control system used in the hydro generator is to regulate the movement of the turbine guide vane, which will affect the electrical power produced by the generator. Here the Guide Vane blade settings can be likened to adjusting the angle of a DC motor. In this study a miniature prototype system governor will be created that is controlled by using a PID controller optimized using the Cuckoo Search Algorithm method. In experiments with the trial error method, the Kp = 3, Ki = 1 and Kd = 10 values with the magnitude of the control parameters obtained the average settling time for set point 4 to set point 8 of 24.2 second. Furthermore, the CSA method is used for tuning the PID. After being tuned to the CSA method the values of Kp, Ki and Kd are different for each set point. For set point 4, Kp = 0.99, Ki = 1.00 and Kd = 0.99, while the average settling time is also better than PID trial error, which is 18.8 second.

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