Sistem Kontrol Governor Menggunakan Pid Yang Dioptimasi Dengan Metode Cuckoo Search Algorithm (Csa)
Governor Control System Using Pid Optimized With the Cuckoo Search Algorithm (Csa)
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(1) * Mochamad Riduwan
Universitas Widyagama Malang
Indonesia
(2) Fachrudin Hunaini Universitas Widyagama Malang
Indonesia
(3) Muh Mukhsim Universitas Widyagama Malang
Indonesia
(*) Corresponding Author
Abstract
Indonesia has enormous potential for the Hydroelectric Power Plant (PLTA). Considering that PLTA is an environmentallyfriendly 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 theGovernoor System in a hydropower plant because of its simple controller. At present hydro power plants still use theconventional 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 PIDparameters. One of them is Cucckoo Search Algorithm (CSA) which is inspired by the behavior of cuckoo birds in placingtheir eggs. By using the CSA method, it is expected to provide a better system response than using the old system PIDcontrol (trial-error). The final goal of the PID control system used in the hydro generator is to regulate the movement ofthe turbine guide vane, which will affect the electrical power produced by the generator. Here the Guide Vane blade settingscan be likened to adjusting the angle of a DC motor. In this study a miniature prototype system governor will be createdthat is controlled by using a PID controller optimized using the Cuckoo Search Algorithm method. In experiments withthe trial error method, the Kp = 3, Ki = 1 and Kd = 10 values with the magnitude of the control parameters obtainedthe 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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Copyright (c) 2019 Mochamad Riduwan, Fachrudin Hunaini, Muh Mukhsim
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