微機(jī)控制原理與技術(shù)實驗指導(dǎo)書-在線瀏覽
2024-08-23 23:14本頁面
【正文】 TLAB描述對象的模型。五：設(shè)計要求已知：M = ；b = ；k = 10N/m 要求： ；指出穩(wěn)態(tài)誤差Ess和調(diào)節(jié)時間Ts。；選取Kp＝50，Ki＝100，用Step函數(shù)求其閉環(huán)響應(yīng)曲線；指出穩(wěn)態(tài)誤差Ess、超調(diào)量和調(diào)節(jié)時間Ts。；選取Kp＝100，Ki＝200，Kd＝10，用Step函數(shù)求其閉環(huán)響應(yīng)曲線；指出穩(wěn)態(tài)誤差Ess、超調(diào)量和調(diào)節(jié)時間Ts。六：實驗步驟，進(jìn)入MATLAB記事本窗口；“**．M”文件，輸入程序，保存“**．M”文件；，運行“**．M”文件；；，觀察、分析時間響應(yīng)曲線的變化。 Designed to control the overall system behavior The threeterm controllerThe transfer function of the PID controller looks like the following: KI = Integral gain s take a look at how the PID controller works in a closedloop system using the schematic shown above. The variable (e) represents the tracking error, the difference between the desired input value (R) and the actual output (Y). This error signal (e) will be sent to the PID controller, and the controller putes both the derivative and the integral of this error signal. The signal (u) just past the controller is now equal to the proportional gain (Kp) times the magnitude of the error plus the integral gain (Ki) times the integral of the error plus the derivative gain (Kd) times the derivative of the error. This signal (u) will be sent to the plant, and the new output (Y) will be obtained. This new output (Y) will be sent back to the sensor again to find the new error signal (e). The controller takes this new error signal and putes its derivative and its integral again. This process goes on and on. The characteristics of P, I, and D controllersA proportional controller (Kp) will have the effect of reducing the rise time and will reduce ,but never eliminate, the steadystate error. An integral control (Ki) will have the effect of eliminating the steadystate error, but it may make the transient response worse. A derivative control (Kd) will have the effect of increasing the stability of the system, reducing the overshoot, and improving the transient response. Effects of each of controllers Kp, Kd, and Ki on a closedloop system are summarized in the table shown below. CL RESPONSERISE TIMEOVERSHOOTSETTLING TIMESS ERRORKpDecreaseIncreaseSmall ChangeDecreaseKiDecreaseIncreaseIncreaseEliminateKdSmall ChangeDecreaseDecreaseSmall ChangeNote that these correlations may not be exactly accurate, because Kp, Ki, and Kd are dependent of each other. In fact, changing one of these variables can change the effect of the other two. For this reason, the table should only be used as a reference when you are determining the values for Ki, Kp and Kd. Example ProblemSuppose we have a simple mass, spring, and damper problem. The modeling equation of this system is (1)Taking the Laplace transform of the modeling equation (1
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