Servo system is widely used in industrial automation, aerospace, robotics, precision machine tools and other fields, and its control accuracy and response speed directly determine the performance of the system. In the servo system, electro-hydraulic servo valve is the key actuator, and PID (Proportional-Integral-Differential) controller has become the most commonly used control algorithm in servo valve control because of its simple structure, convenient adjustment and strong applicability. However, the performance of PID control is highly dependent on parameter tuning. In this paper, the tuning methods of three parameters in servo valve PID control are discussed.
First, the basic principle of PID control
By calculating the deviation between the current output of the system and the expected value, and combining the weighting of the three parts, PID controller outputs control signals to adjust the actuator. Its mathematical expression is:
[
u(t) = K_p e(t) + K_i int_0^t e( au) d au + K_d frac{de(t)}{dt}
]
Among them:
-( K_p ) is the proportional gain, which determines the response speed;
-( K_i ) is the integral gain, which is used to eliminate the steady-state error;
-( K_d ) is differential gain, which is used to suppress overshoot and oscillation.
Second, the characteristics of servo valve control system
Servo valve control usually involves hydraulic power system, which has the characteristics of large inertia, obvious response delay and obvious nonlinear characteristics. Therefore, PID parameter tuning should not only consider the rapid response of the system, but also take into account the stability and anti-interference ability.
Third, the common methods of PID parameter tuning
1. Empirical trial and error method
This is the most commonly used method, and the operator constantly adjusts the parameter values according to the system response until a satisfactory control effect is achieved. The general steps are:
-Set ( K_i = 0 ) and ( K_d = 0 ) first, and gradually increase ( K_p ) until the system starts to oscillate;
-Add the integral term ( K_i ) to eliminate the steady-state error;
-Finally, the differential term ( K_d ) is added to suppress oscillation and improve system stability.
2. Ziegler-Nichols method
This method is set based on critical gain ( K_c ) and critical period ( T_c ). By increasing ( K_p ) until the system oscillates with equal amplitude, record ( K_c ) and oscillation period ( T_c ) at this time, and then set ( K_p, K_i, K_d ) according to the empirical formula. This method is suitable for linear and time-invariant systems, but it needs to be modified in actual servo systems.
3. Frequency domain analysis and model identification method
The mathematical model of servo valve control system is established by using frequency response analysis or system identification technology, and then PID parameters are designed by pole configuration and gain phase margin. This method has high accuracy, but it requires high system modeling.
4. Self-tuning and intelligent optimization method
With the development of intelligent control technology, such as fuzzy PID, neural network PID, genetic algorithm, etc. are also used for automatic tuning of PID parameters, which can adapt to the changes of system parameters and nonlinear effects and improve control performance.
Fourth, common problems and countermeasures in parameter adjustment
-Overshoot is too large: decrease ( K_p ) or increase (k _ d ) appropriately;
-Too slow response: increase ( K_p ) or (k _ i );
-There is a steady-state error: the integration is enhanced (k _ i );
-Violent oscillation: decrease ( K_p ) and increase ( K_d ).
V. Conclusion
Parameter tuning of servo valve PID control is a complex and critical process, which directly affects the dynamic performance and stability of the system. In practical application, we should combine the system characteristics, field debugging experience and advanced algorithm, choose the appropriate setting method, and constantly optimize and adjust it to achieve the control goal of high precision, high speed and high stability. With the development of control theory and computer technology, PID parameter tuning will be more intelligent and automatic in the future.