Siemens S7-300PLC PID function block application experience - Database & Sql Blog Articles

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1, can be automatically set in the software;
2, the automatic tuning of the PID parameters may not be the best for the system, you need to manually adjust the experience. If the P parameter is too small, the time to achieve dynamic balance will be too long; if the P parameter is too large, it will easily produce overshoot.
The problem that the PID function block should pay attention to in the ladder diagram (program):
1. It is better to use the PID wizard to generate the PID function block;
2, I want to say one of the simplest and most easily overlooked problems, that is: the PID function block enable control can only use SM0.0 or any one of the memory's normally open contacts in parallel with the memory's normally closed A never-ending contact like a contact!
In the previous engineering debugging, the author encountered such a problem: the PID function block has normal time action, and the time action is abnormal, and when the abnormality is found, the PID function block is no problem (the PID parameter is correct and the correct function is enabled). There is no output. Finally checked for a long time, suddenly realized that it may be the problem of enabling - I connected the start/stop control of the relay in the enable side, I changed it to SM0.0, everything is normal!
At the same time, I also understand that the PID function block has normal time action and there is a time delay. The reason is that sometimes the relay is in the action state after filling the program, there will be no problem. Once the device is stopped, there will be a problem - PID function Once the block enable is disconnected, the work will not work properly!
Tell this to everyone to avoid the same mistakes.
The following is a general method for parameter tuning of PID controllers:
The parameter tuning of the PID controller is the core content of the control system design. It determines the scale factor, integration time and derivative time of the PID controller according to the characteristics of the controlled process. There are many methods for PID controller parameter tuning. There are two general categories: one is the theoretical calculation tuning method. It is mainly based on the mathematical model of the system, and the controller parameters are determined through theoretical calculations. The calculation data obtained by this method may not be directly usable, and must be adjusted and modified through engineering practice. The second is the engineering setting method, which relies mainly on engineering experience and is directly carried out in the test of the control system. The method is simple and easy to grasp, and is widely used in engineering practice. The engineering tuning method of PID controller parameters mainly includes critical ratio method, reaction curve method and attenuation method. Each of the three methods has its own characteristics, and the common point is to pass the test, and then adjust the controller parameters according to the engineering experience formula. However, no matter which method is used, the controller parameters need to be adjusted and improved in actual operation. The critical ratio method is generally used now. The tuning steps of the PID controller parameters using the method are as follows: (1) first select a sufficiently short sampling period for the system to work; (2) only add the proportional control link until the system has a critical oscillation in the step response of the input. Write down the proportional amplification factor and the critical oscillation period at this time; (3) Calculate the parameters of the PID controller by the formula under a certain degree of control.
PID parameter setting: It is based on the familiarity of experience and technology, and the measurement value tracking and set value curve are referenced to adjust the size of P\I\D.
Proportion I / differential D = 2, the specific value can be determined according to the instrument, then adjust the proportional band P, P over the head, reach a stable time, P is too short, will oscillate, never hit the set requirements.
The engineering tuning of PID controller parameters, the empirical data of PID parameters in various adjustment systems can be referred to below:
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.
Commonly used on the book:
Parameter tuning to find the best, from small to large order;
First, the ratio is post-integrated, and finally the differential is added;
The curve oscillates frequently, and the proportional disk is enlarged;
The curve floats around the big bay, and the proportional disk is small;
The curve deviates from the recovery slowly, and the integration time decreases;
The curve has a long fluctuation period and the integration time is lengthened;
The curve oscillates at a fast frequency, first reducing the differential;
The momentum is large and the fluctuations are slow. The differential time should be lengthened;
Two waves of ideal curve, 4 to 1 lower than the front height;
When you look at the two-tone analysis, the quality of the adjustment will not be low.
After years of work experience, I personally think that the size of the PID parameters is determined on the one hand according to the specific circumstances of the control object; on the other hand, experience. P is to solve the amplitude oscillation, P will have a large amplitude oscillation, but the oscillation frequency is small, the system reaches a stable time; I is to solve the speed of the action response, I is slower, and vice versa. ; D is to eliminate static errors, the general D settings are relatively small, and the impact on the system is relatively small. For temperature control system P between 5-10%; I between 180-240s; D below 30. For pressure control system P between 30-60%; I between 30-90s; D below 30.
Here is a method of experience. This method is essentially a trial and error method. It is an effective method that has been summarized in production practice and has been widely used in the field.
The basic procedure of this method is to first determine a set of regulator parameters based on operating experience, and put the system into closed-loop operation, and then artificially add step disturbances (such as changing the set value of the regulator) to observe the adjusted or adjusted The step response curve of the output. If the control quality is considered unsatisfactory, the regulator parameters are changed according to the influence of each tuning parameter on the control process. Repeat the test in this way until you are satisfied.
The empirical method is simple and reliable, but it requires a certain amount of on-site operation experience. The timing is easy to be subjective and one-sided. When the PID regulator is used, there are a plurality of tuning parameters, and the number of trial and error times is increased, and it is difficult to obtain an optimum tuning parameter.
Take the PID regulator as an example to illustrate the tuning steps of the empirical method:
A. Let the regulator parameter integral coefficient S0=0, the actual differential coefficient k=0, the control system enters the closed-loop operation, change the proportional coefficient S1 from small to large, let the disturbance signal make a step change, observe the control process until it is satisfactory. Control process up to now.
B. Take the proportional coefficient S1 and multiply the current value by 0.83. Increase the integral coefficient S0 from small to large, and let the disturbance signal make a step change until a satisfactory control process is obtained.
C. The integral coefficient S0 remains unchanged, change the proportional coefficient S1, observe whether the control process is improved, and if there is improvement, continue to adjust until it is satisfied. Otherwise, the original proportional coefficient S1 is increased a little, and then the integral coefficient S0 is adjusted to improve the control process. Try again and again until you find a satisfactory scale factor S1 and integral coefficient S0.
D. Introduce the appropriate actual differential coefficient k and the actual differential time TD, at which time the scale factor S1 and the integral coefficient S0 can be appropriately increased. As with the previous steps, the tuning time adjustment needs to be adjusted repeatedly until the control process is satisfactory.
The PID parameters are determined based on the inertia of the control object. Large inertia such as: temperature control of large drying room, generally P can be above 10, I=3-10, D=1. Small inertia such as: a small motor with a water pump for pressure closed-loop control, generally only with PI control. P = 1-10, I = 0.1-1, D = 0, these are to be corrected when debugging in the field.
PID control instructions:
In engineering practice, the most widely used regulator control law is proportional, integral, differential control, referred to as PID control, also known as PID adjustment. The PID controller has been in existence for nearly 70 years. It has become one of the main technologies of industrial control because of its simple structure, good stability, reliable operation and convenient adjustment. When the structure and parameters of the controlled object cannot be fully grasped, or the precise mathematical model is not obtained, when other techniques of control theory are difficult to adopt, the structure and parameters of the system controller must be determined by experience and on-site debugging. PID control technology is the most convenient. That is, when we do not fully understand a system and controlled objects, or can not obtain system parameters through effective measurement methods, it is most suitable to use PID control technology. PID control, in practice, also has PI and PD control. The PID controller is based on the error of the system, and uses the proportional, integral, and differential calculations to control the amount of control.
Proportional (P) control: Proportional control is one of the simplest methods of control. The output of its controller is proportional to the input error signal. There is a steady state error in the system output when there is only proportional control.
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 entering the steady state, the control system is said to have a steady state error or simply a poor system. In order to eliminate the steady-state error, an "integral term" must be introduced in the controller. The integral term versus the error is integrated over time, and as time increases, the integral term increases. Thus, even if the error is small, the integral term increases with time, which pushes the controller's output up so that the steady-state error is further reduced until it equals zero. Therefore, the proportional + integral (PI) controller can make the system have no steady-state error after entering the steady state.
Differential (D) control: In differential control, the output of the controller is proportional to the differential of the input error signal (ie, the rate of change of the error). The automatic control system may experience oscillation or even instability during the adjustment of the overcoming error. The reason is that there is a large inertia component (link) or a hysteresis component, which has the effect of suppressing the error, and the change always lags behind the error. The solution is to make the change of the effect of the suppression error "advance", that is, when the error is close to zero, the effect of suppressing the error should be zero. That is to say, it is often not enough to introduce only the "proportional" term in the controller. The proportional term is only the amplitude of the amplification error, and the current need to increase is the "differential term", which can predict the trend of error variation. In this way, the controller with proportional + differential can make the control effect of the suppression error equal to zero or even a negative value in advance, thereby avoiding the serious overshoot of the controlled amount. Therefore, for controlled objects with large inertia or hysteresis, the proportional + derivative (PD) controller can improve the dynamic characteristics of the system during the adjustment process.