Control principle of air cushion headbox

The air cushion headbox control system mainly controls the pressure and liquid level inside the headbox. By adjusting the rotational speed of the flushing pump and the Roots blower, the sizing amount of the flushing pump and the amount of air blown by the Roots blower will be changed. These two quantities mainly affect the pressure and level of the headbox. The pressure in the box is generated partly by the pulp and partly by the air, and the pressure determines the speed of the pulp sprayed from the headbox to the forming wire. In the headbox control system, the mathematical model of the pressure and liquid level of the controlled object is difficult to establish, and the control structure may change at any time. Fuzzy control is to write the operator's long-term operating experience into fuzzy language. Once the field signal is input to the control system, the fuzzy controller will combine the control experience to obtain the output value. Because there is a coupling relationship between the input and output in the pressure and liquid level of the controlled object, this topic combines the decoupling control function of the fuzzy control itself to design a fuzzy decoupling controller, and adjust the control system by on-site. PID parameters to achieve good control effect.

Control System Analysis and Controller Design

Control System Analysis

The pressure and liquid level of the air-cushion headbox control system have serious coupling and nonlinearity. When the vehicle speed is low (below 300m/min), the control requirements can be basically met without decoupling control. However, when the vehicle speed is high, the slight fluctuation of the system will have a greater impact on the system, so the solution Coupling control is essential in this case. When applying a general decoupled controller, the mathematical model of the plant needs to be known. With the continuous development of control technology, the controlled object has become more and more complex, and the control precision is very high, so the design of the decoupling controller has become very cumbersome and complicated. Due to the difficulty in obtaining the mathematical model of the controlled object, it is also difficult to design a decoupled controller. At the same time, the decoupling controller has poor adaptability and poor robustness. Therefore, a decoupling controller with simple design, independent of the mathematical model of the controlled object, strong adaptability and good robustness is required. Combining these characteristics, fuzzy controller is a very suitable choice. The fuzzy controller itself has the function of decoupling, which not only overcomes the shortcomings of the traditional decoupling controller but also has many advantages of fuzzy control.