Common PID mnemonics:

Thread Content

1. Common mnemonic for PID: Find the optimal parameter setting by checking in ascending order from small to large； First ratio, then integration, and finally adding the derivative ； The curve oscillates very frequently; the scale dial needs to be enlarged ； The curve floats around the large bay; turn the scale dial inwards ； The curve deviates slowly from its original state, and the integration time decreases ； The curve has a long fluctuation period, so the integration time needs to be increased further ； The curve oscillates at a high frequency; first reduce the derivative ； Large error variation leads to slow fluctuations; the differentiation time should be increased ； For the ideal curve, two waves with a higher peak at the front and a lower one at the back in a 4-to-1 ratio is preferable. 2. Observe first, adjust second, and conduct thorough analysis – this ensures high control quality. 2. For the engineering tuning of PID controller parameters, the following are some empirical values for P.I.D parameters in various control systems: Temperature T: P=20~60%, T=180~600s, D=3-180s; Pressure P: P=30~70%, T=24~180s; Liquid level L: P=20~80%, T=60~300s; Flow rate L: P=40~100%, T=6~60s. 3. Principles and characteristics of PID control In practical engineering applications, the most widely used control laws are proportional, integral, and derivative control, commonly referred to as PID control, or PID regulation. The PID controller has been around for nearly 70 years, and thanks to its simple structure, good stability, reliable performance, and ease of adjustment, it has become one of the key technologies in industrial control. When the structure and parameters of the controlled object cannot be fully understood, or an accurate mathematical model is not available, and other techniques from control theory cannot be applied, the structure and parameters of the system controller must be determined based on experience and on-site tuning; in such cases, PID control technology is the most convenient to use. That is, when we do not fully understand a system and its controlled object, or when it is not possible to obtain the system parameters through effective measurement methods, PID control technology is the most suitable approach. There is PID control; in practice, there are also PI and PD control. A PID controller controls the system by calculating the control amount using proportion, integration, and differentiation based on the system’s error. 　Proportional (P) control Proportional control is the simplest form of control. The output of its controller is proportional to the input error signal. When only proportional control is used, there is a steady-state error in the system output. 　Integral (I) control: In integral control, the output of the controller is proportional to the integral of the input error signal. For an automatic control system, if there is a steady-state error after it reaches steady state, then such a control system is said to have a steady-state error, or simply referred to as a system with steady-state error. To eliminate steady-state error, an “integral term” must be introduced into the controller. The integral term represents the time-dependent integration of the error, and as time increases, this integral term grows. In this way, even if the error is small, the integral term increases over time; it drives the output of the controller to increase, thereby further reducing the steady-state error until it becomes zero. Therefore, a proportional-plus-integral (PI) controller enables the system to have no steady-state error after reaching steady state. 　Differential (D) control: In differential control, the output of the controller is proportional to the derivative of the input error signal (i.e., the rate of change of the error). Automatic control systems may experience oscillations or even instability during the process of correcting errors. The reason is the presence of components with large inertia or components that introduce delay, which have the effect of suppressing errors; their changes always lag behind those of the errors. The solution is to make the change in the error-suppression effect \"proactive\", that is, when the error approaches zero, the error-suppression effect should be zero. In other words, it is often not sufficient to include only a \"proportional\" term in the controller; the function of this proportional term is merely to amplify the magnitude of the error. What is needed now is a \"derivative\" term, which can predict the trend of error changes. Thus, a controller with both proportional and derivative terms can bring the control action to eliminate the error to zero, or even to a negative value, thereby preventing severe overshoot of the controlled variable. Therefore, for controlled objects with high inertia or lag, a proportional-plus-differential (PD) controller can improve the dynamic characteristics of the system during the regulation process.