系统管理员使用优化的Pid使用布谷鸟搜索算法(Csa)

M. Riduwan, Fachrudin Hunaini, Muhammad Mukhsim
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引用次数: 1

摘要

印度尼西亚在水力发电厂(PLTA)方面具有巨大潜力。考虑到PLTA是一个环境友好型电厂,该电厂的组件值得进一步发展。其中之一就是水电调速器控制系统的研制。PID控制器由于其控制方法简单,是水电站调速器控制中常用的一种控制系统。目前水电厂仍采用传统的PID控制方法进行平均试错。该方法参数调整困难,耗时长,控制精度差。因此,需要一种聪明的方法来克服这个问题。在过去的几年里,研究人员已经使用了许多智能方法(人工智能)来确定直流pid参数。其中之一是布谷鸟搜索算法(CSA),该算法的灵感来自布谷鸟产卵的行为。通过使用CSA方法,期望提供比使用旧系统PIDcontrol(试错)更好的系统响应。水轮发电机中使用的PID控制系统的最终目的是调节水轮导叶的运动,这将影响发电机产生的电力。这里的导叶叶片设置可以比作调整直流电机的角度。在本研究中,将创建一个微型原型系统调速器,该调速器采用杜鹃搜索算法优化的PID控制器进行控制。在试差法实验中,当Kp = 3、Ki = 1、Kd = 10的值与控制参数的量级相等时,得到设定点4至设定点8的平均沉降时间为24.2 s。此外,采用CSA方法对PID进行整定。调整为CSA方法后,每个设定点的Kp、Ki和Kd值不同。设定点4 Kp = 0.99, Ki = 1.00, Kd = 0.99,平均沉降时间也优于PID试验误差,为18.8 s。
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Sistem Kontrol Governor Menggunakan Pid Yang Dioptimasi Dengan Metode Cuckoo Search Algorithm (Csa)
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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