Abstract: This paper designs a simulation system for the impact of power grid fluctuations on the speed control of a brushless DC motor, based on the powerful image design and processing capabilities of LabVIEW/CVI. An extended critical proportional method is used for tuning digital PID control to reduce this impact. Practice shows that the system can effectively simulate the influence of power grid fluctuations on the speed control of a brushless DC motor and provides valuable reference for the calculation of power grid parameters. Keywords: Lab windows/CVI; power grid fluctuations; digital PID; brushless DC motor; simulation [b][align=center]Research on Lab windows/CVI-based brushless DC motor speed control system simulation LI Yadong, YANG Guanlu[/align][/b] Abstract This thesis is based on the powerful design and image processing functions of Lab windows/CVI, and devises a simulation system of the power grid fluctuations of the brushless DC motor speed control. It also expands the use of the critical method of setting the digital PID control to reduce the impact. Practice shows that the system can effectively simulate the influence of grid fluctuations on the speed of the brushless DC motor, and it provides reference value for grid computing. Key words Lab windows/CVI; Fluctuations in power system; Digital PID; brushless DC motor; simulation 0. Introduction Brushless DC motors eliminate the mechanical commutation device of ordinary DC motors and replace it with electronic commutation. This gives them the advantages of easy control of DC motors and the simple structure and low cost of asynchronous motors, thus leading to their widespread application. How to optimally control its rotation speed is still a hot topic of exploration [2]. Lab Windows/CVI is an interactive C language development environment. It takes ANSIC as its core and organically combines the powerful and flexible C language with measurement and control professional tools for data acquisition, analysis and display. Its integrated development environment, interactive programming method, function panel and rich library functions greatly enhance the function of C language and provide an ideal software development environment for developers familiar with C language to develop detection, data acquisition, process monitoring and other systems [1]. With social progress and technological development, the power grid load is constantly increasing and the power grid pollution is becoming more and more serious. The research on the impact of power grid fluctuations on load is showing its importance. PID control is one of the earliest developed control strategies. Due to its simple algorithm and high reliability, it is widely used in process control and motion control. However, actual industrial production processes often exhibit nonlinearity and time-varying uncertainty, making it difficult to establish accurate mathematical models. Applying classic PID controllers often fails to achieve ideal control results, necessitating improvements to classic PID control and effective tuning. This paper leverages the powerful capabilities of LabWindows/CVI to simulate the impact of power grid fluctuations on the speed of a brushless DC motor, and employs extended critical proportional method-tuned digital PID control to mitigate this impact. 1. Control System Principles and System Framework 1.1 Digital PID Control PID control combines the proportional (P), integral (I), and derivative (D) components of the deviation linearly to form the control quantity, which is then used to control the controlled object. Such a controller is called a PID controller. The integrator eliminates steady-state error and improves accuracy, but slows down the system's response speed and reduces stability. The derivative increases stability and speeds up the response. The proportional component is the fundamental element. Using all three components together, and selecting appropriate parameters, stable control can be achieved. PID controllers have a simple structure, easily adjustable parameters, and do not necessarily require an exact digital model of the system; therefore, they are widely used in industry. The PID controller first appeared in the analog control system. The traditional analog PID controller realizes its function through hardware (electronic components, pneumatic and hydraulic components). With the advent of computers, it was transplanted into the computer control system. The parameters can be adjusted online according to experiments and experience, so better control performance can be obtained. 1.1.1 The PID controller adopts the traditional incremental digital PID control [3]: (1) Where K[sub]P[/sub] is the proportional amplification factor; K[sub]I[/sub] is the integral time constant; K[sub]D[/sub] is the derivative time constant. 1.1.2 Assuming the thyristor rectification model is adopted, the sampling period is 10ms, i.e.: (in is the grid voltage input) (2) 1.1.3 Establishment of brushless DC motor model [4] The equation of a three-phase three-state brushless DC motor with one phase conducting is: (3) Armature circuit voltage balance equation: (4) Where: L[sub]α[/sub] is the phase winding inductance, R[sub]α[/sub] is the phase winding resistance, l[sub]v[/sub] is the electromotive force constant, and ω is the angular velocity of the rotor rotation. Torque balance equation: (5) Where: T[sub]em[/sub] is the electromagnetic torque, T[sub]1[/sub] is the load torque, B is the damping coefficient, J is the moment of inertia, and k[sub]1[/sub] is the torque constant. From the above equations, the state space of the brushless DC motor can be obtained (6) 1.1.4 The overall software flowchart is roughly as shown in Figure 1: [align=center] Figure 1 Overall Flowchart[/align] 1.2 Selection of Digital PID Tuning Method The tuning of PID parameters generally adopts the trial-and-error method, the empirical data method, or the engineering tuning method. The engineering tuning method mainly includes the extended critical proportional method, the extended response curve method, the normalized parameter tuning method, etc. This system uses the extended critical proportional method. The extended critical proportional method is suitable for controlled objects with self-balancing properties. The tuning steps are as follows: (1) First, select the regulator as a pure proportional regulator to form a closed loop. Change the proportional coefficient K[sub]P[/sub] from small to large so that the system response to the step input reaches the critical oscillation state (stable edge). The proportional coefficient at this time is recorded as K[sub]γ[/sub], and the period of the critical oscillation is recorded as T[sub]γ[/sub]. The selection of K[sub]γ[/sub] and T[sub]γ[/sub] can be achieved by Lab Windows/CVI virtual instrument programming. (2) According to the empirical formula [5] provided by Ziegler-Nichols (Figure 2), the PID regulator parameters can be obtained from these two reference parameters. [align=center] Figure 2 Empirical formula[/align] Software flowchart for programming to obtain K[sub]γ[/sub] and T[sub]γ[/sub] (Figure 3). [align=center] Figure 3 Software flowchart for PID tuning[/align] 1.3 System block diagram The control block diagram of the entire DC motor speed control simulation system is shown in Figure 4. The main part is completed by digital PID control. [align=center] Figure 4 Control block diagram[/align] We know that the input voltage of the DC motor is determined by the AC power input from the grid and the firing angle of the thyristor phase control. According to this principle, when the grid fluctuates, the output of the digital PID controls the phase control circuit of the thyristor, so that the speed of the DC motor is stabilized at the rated speed. However, according to this principle, if the AC voltage is too low, it may not be able to drive the motor to the rated speed. Therefore, this system uses the sum of the PID output and the rectified voltage as the input of the motor, which can also achieve the purpose of controlling the motor. 2 Software Function Introduction The main interface of this software is shown in Figure 5. According to the function, it can be divided into waveform display area, waveform processing area and control area. (1) Waveform display area. It consists of waveform display screen and tachometer. The speed change of DC motor can be observed. The red speed change curve can be seen from the figure. (2) Waveform processing area. The output waveform is processed using the processing function of Lab Windows/CVI. It has the functions of scaling, panning, graphic printing and waveform saving. In this area, the overshoot and adjustment time can also be displayed. These two important indicators are helpful for verifying the experimental results. If you want to connect to the database server, you can click the "Network Parameters" setting button in this area. (3) Control area. All control functions and control parameters are input from the control area. This system uses PID control. K_P, K_I, K_D parameters and the expected speed can be input from the control area; starting and stopping the motor are also done in the control area. [align=center]Figure 5 Main Interface of the Software[/align] 3 Operation of the Software This system includes three software programs: Test Grid (GRID.exe), DC Motor Control (DC Motor Control.exe), and Test Database (DB.exe). The Test Grid simulates mains power input from the grid, and the Test Database simulates receiving motor parameters from a database server. During operation, open DB.exe, DC Motor Control.exe, and GRID.exe in sequence. If the latter two display "Connection to server failed," change the IP address on their interfaces to the IP address of the computer where DB.exe and DC Motor Control.exe are located, and then manually connect. All control operations are located in the control area shown in Figure 5. "Start Motor" simulates the motor operating under the KP, KI, and KD parameters shown in the diagram; "Stop Motor" stops the motor from rotating; "Motor Parameters" allows modification of motor parameters and conversion to transfer function form; "Network Parameters" allows viewing network connection status and manually establishing and connecting to the database server; "PID Parameter Tuning" allows engineering tuning of the motor model using the extended critical proportional method to obtain suitable KP, KI, and KD parameters; "Close Instrument" closes the software. In addition, the software includes some user-friendly operations, such as menus, pop-up windows when right-clicking the software interface or graphics display area, saving graphics, printing graphics, and scaling graphics. 4. Conclusion In summary, virtual instruments are an organic combination of traditional electronic instruments and computer technology, possessing advantages unmatched by traditional instruments. This paper uses LabVIEW/CVI to design a simulation system software for brushless DC motor speed control. This system serves as a reference for power system simulation and grid parameter calculation. It receives voltage data from the grid, processes it using digital PID control, and then sends speed, voltage, and current parameters via the network to a database server. These parameters are stored in the database, and appropriate control parameters are selected based on this data. Through debugging, the brushless DC motor speed control simulation runs normally, and the extended critical proportional method significantly optimizes the PID parameter settling time. This paper successfully combines CVI programming with digital PID control, using CVI programming to simulate the impact of grid fluctuations on the speed of a brushless DC motor, and finding an effective PID parameter tuning method. The results provide valuable reference for power system simulation and grid parameter calculation. References [1] Song Yufeng et al., Lab Windows/CVI Step-by-Step In-Depth and Development Examples [M] Beijing: Machinery Industry Press, 2003 [2] Zhang Jizu. Speed ​​Control of Brushless DC Motor Based on DSP and Active Disturbance Rejection Controller [J]. Master's Thesis of Xi'an University of Technology, 2007.3 [3] He Kezhong, Li Wei. Computer Control System [M] Beijing: Tsinghua University Press, 1998 [4] Song Shoujun, Liu Jinglin. Modeling of Brushless DC Motor and Simulation of Modern Speed ​​Regulation Method [J]. Micromotors 2004, 09: 21-24 [5] Chen Chuanshuo, Tian Lihua. Tuning Method of PID Control Parameters [J]. Journal of Changchun University of Posts and Telecommunications, 1994, Vol.12 No.1 Author Introduction: Li Yadong (1982-), male (Han nationality), from Henan, postgraduate of the 2006 class of the School of Information Science and Technology of Huaqiao University, majoring in Electrical Engineering Theory and New Technology, mainly researching induction heating power supply and virtual instruments.