summary
An electro-hydraulic proportional directional valve was used to design an electro-hydraulic position servo control system. Real-time control was achieved using a hybrid programming approach combining LabVIEW and MATLAB. A personal computer served as the digital controller, and an NI data acquisition card was employed to handle data acquisition, output control, and other functions. A mathematical model was established to address the characteristics of the electro-hydraulic proportional position control system. To compensate for system instability, a PID control algorithm was used to correct for it, improving the system's accuracy and response speed.
Foreword
Electro-hydraulic position servo systems are the most basic and commonly used type of hydraulic servo system, used in applications such as machine tool table positioning, strip thickness control in strip mills, strip misalignment control, aircraft and ship steering gear control, radar and artillery control systems, and vibration test benches. In control systems for other physical quantities, such as speed and force control systems, position control loops are often used as components within a larger loop.
Electro-hydraulic position servo systems are primarily used to solve position tracking control problems. Their fundamental task is to achieve timely and accurate tracking of the controlled variable to the given variable through an actuator, while maintaining sufficient control precision. The dynamic characteristics of an electro-hydraulic servo system are a crucial indicator for evaluating its design and debugging level. It consists of an electrical signal processing unit and several hydraulic components. The dynamic performance of these components interacts and restricts each other, and the system itself contains nonlinearities, resulting in complex dynamic performance. Therefore, the design and simulation of electro-hydraulic servo control systems are receiving increasing attention.
This paper implements position control of a servo cylinder using a proportional directional valve, and incorporates a displacement sensor to form a closed-loop position control system. A NI USB-6008 data acquisition card is used to complete multiple functions such as data acquisition and data output control. Good real-time control functionality is achieved through mixed programming of LabVIEW and MATLAB.
1. Electro-hydraulic servo system principle and modeling
1.1 Composition and Principle of Electro-hydraulic Servo System
The electro-hydraulic position servo control system uses liquid as the power transmission and control medium, and utilizes electrical signals for control input and feedback. As long as a specific input signal is input, the actuator can start and quickly and accurately reproduce the change pattern of the input quantity. The control system structure diagram is shown in Figure 1.
Figure 1. Structure diagram of electro-hydraulic position servo control system
1.2 Modeling of Electro-hydraulic Position Servo System
The electro-hydraulic proportional directional valve in this system is BFW-03-3C2-95-50, with a nominal diameter of 10mm, a maximum working pressure of 31.5MPa, and a maximum flow rate of 50l/min. The hydraulic cylinder piston stroke is 20mm. According to the national standard GB2349-80 piston rod piston series, the inner diameter D is 63mm, and the effective working area is 3.0×10-3m2. The displacement sensor selected is a WDL200 linear sliding conductive plastic potentiometer, with the following performance parameters: 0-5V output, measurement range 0-200mm, resolution 0.01mm, and linearity 0.2%.
1.2.1 Modeling of Valve-Controlled Servo Cylinders
(1) Linearized flow equation for proportional valve
QL=Kqxv−KcpL（1）
In the formula, Kq represents the flow gain of the proportional valve; Kc represents the flow-pressure coefficient of the proportional valve; pL represents the load pressure; and xv represents the displacement of the proportional valve spool.
(2) Continuity equation of servo cylinder flow rate
2. MATLAB Simulation Based on PID Control
The performance of a conventional PID controller depends on the tuning of parameters Kp, Ki, and Kd. Better parameter tuning results in better control, and vice versa. There are generally two methods for parameter tuning: theoretical design and experimental determination. Through extensive experimentation, the PID parameters chosen were: Kp=1.1, Ki=0.2, and Kd=0.01. The simulation results in Simulink are shown in the figure.
Figure 3 Simulation diagram of PID control
3. LabVIEW-based real-time control software
The LabVIEW online control process begins with data acquisition. The acquired data is the displacement from the displacement sensor, which is converted into voltage and sent to the analog input terminal AI0 of the data acquisition card. The program configures the analog input channel, including the sampling channel number, maximum and minimum values, and sampling mode (differential or single-ended), and outputs the sampled waveform. Next, the PID algorithm is used, setting the parameters of P, I, and D, as well as the upper and lower limits of the output. Then, the analog output is configured. The program configures the analog output channel, setting the output port to AO0 and configuring the maximum and minimum values. The calculated value is sent to the input of the servo amplifier, driving the servo valve to move the hydraulic cylinder forward or backward, thus completing the position control of the electro-hydraulic servo system. The data acquisition system flowchart is shown in Figure 4.
Figure 4. Data Acquisition System Flowchart
During data acquisition, the front panel is configured with physical channels, maximum and minimum values for analog inputs, and single-ended configuration. Real-time waveform curves of the acquired data are plotted. In this experiment, the object of real-time data acquisition is the feedback value from the displacement sensor, which is sent to the analog input terminal of the N1-6008 data acquisition card. The acquisition system subroutine is shown in Figure 5.
Figure 5. Flowchart of the data acquisition subroutine
4. Conclusion
The reliability verification of the system was achieved using MATLAB/Simulink simulation, accurately simulating the actual system's operating state. LABVIEW visual programming further simplifies system operation. The modeling process and simulation results demonstrate that establishing a correct mathematical model and conducting analysis and simulation of the system's dynamic characteristics can effectively predict the system's output, achieving an understanding of the system's operating state. This improves the efficiency of system design and analysis, laying a foundation for further control system development and enhancing response speed and control accuracy.
For more information, please visit the Server Systems channel.
