Abstract: Currently, the pH value of ash water discharged from coal-fired power plants generally exceeds the standard. To address the characteristics of nonlinearity, time-varying nature, large time delay, and tight coupling of multiple variables in the control process, a fuzzy control scheme is adopted. The usage of the Fuzzy Logic for G Toolkit based on LabVIEW is introduced, and a fuzzy controller is designed using it. Combined with the LabVIEW development platform, a fuzzy control system for ash water pH is designed, achieving effective control of ash water pH. Keywords: Fuzzy control; LabVIEW; Fuzzy Logic Toolkit; Ash water pH 1. Introduction Currently, hydraulic ash removal is the main method used in China's thermal power plants. When alkaline substances such as active calcium oxide in coal ash come into contact with the ash water, they dissolve in the water, causing the pH value of the ash water to rise and exceed the standard. The common method for treatment is to neutralize with acid. Due to the severe nonlinearity, time delay, and nonparametric model of the neutralization process, it is difficult to achieve ideal results by using conventional control techniques such as PID to precisely control the pH value. However, for such nonlinear, strongly coupled, time-delayed, and difficult-to-establish accurate mathematical models, fuzzy control can achieve better results [1]. Virtual instruments are a new generation of virtual measurement and control instruments based on personal computers. They use the display function of computer monitors to simulate the control panel of traditional instruments, output the detection results in various forms, and use the powerful software functions of computers to realize the calculation, analysis, and processing of signal data. The I/O interface devices complete the acquisition, measurement, and conditioning of signals. LabVIEW is a highly efficient virtual instrument development tool based on graphical programming designed for scientists and engineers. Here, LabVIEW is used as the development platform, and the fuzzy logic toolbox is used to quickly and conveniently design a fuzzy control system for pH of power plant ash water. 2. Process Flow and Control Principle The system adopts an industrial computer control method. The collected pH and flow signals of the ash water are sent to the industrial computer. The industrial computer then calculates the required acid addition based on the set pH control range and converts it into a 4-20mA adjustment signal, which is sent to the signal converter to control the speed of the electromagnetic metering pump, thereby adjusting the acid addition and achieving the goal of meeting the pH value of the ash field drainage. The process flow and control principle are shown in Figure 1. [align=center] Figure 1 System Process Flow and Control Principle[/align] 3. Software Design A virtual instrument system runs on the industrial computer for fuzzy control and displays the instantaneous flow rate and pH value of the monitored ash water. The fuzzy controller is the core of the entire system. The design process of the fuzzy controller based on the LabVIEW platform is described in detail below. 3.1 Software Development Platform LabVIEW and its Fuzzy Logic Toolkit LabVIEW is a graphical programming environment developed by National Instruments (NI) for data acquisition, instrument control, data analysis and data representation. It is designed for test engineers rather than professional programmers. Programming is very convenient, the human-computer interaction interface is intuitive and friendly, and it has powerful data visualization analysis and instrument control capabilities. LabVIEW's Fuzzy Logic for G Toolkit is used to design rule-based fuzzy controllers [2]. Its main application areas are industrial process control and expert systems. It consists of 4 sub-VIs: ① Fuzzy Logic Controller Design VI It is a VI that runs independently in the LabVIEW environment. It consists of three parts: fuzzy membership function editor, fuzzy rule base editor and input/output performance test. It provides a friendly human-computer interaction interface. Users can intuitively and conveniently design various fuzzy logic controllers that meet different requirements. The fuzzy controller designed by this VI is saved in a data file with the suffix .fc and is used to be called by the control system. ② Load Fuzzy Controller VI This VI is used as a graphical function module in the block diagram program and is connected to the Fuzzy Controller VI. When the program starts running, it loads the control parameters stored in the data file with the suffix .fc into the Fuzzy Controller VI. ③ Fuzzy Controller VI This VI is the implementer of the fuzzy controller in LabVIEW. It is used in the block diagram program of LabVIEW, reads the fuzzy controller parameters, and outputs the corresponding results. Each controller has a maximum of four inputs and one output. ④ Test Fuzzy Control VI It is mainly used to test the basic performance of the fuzzy controller. 3.2 Design of Fuzzy Controller The implementation of a typical fuzzy controller needs to solve the following problems: (1) Fuzzification, that is, the setting of membership functions, including the number, shape, position distribution, and degree of overlap of membership functions; (2) Determination of control rules; (3) Fuzzy algorithm; (4) Defuzzification [3]. The fuzzy controller adopts a "two-input, one-output" design. The input variables are the deviation *e* between the detected pH2 value of the grey water and the given pH value of the qualified grey water, and the rate of change of the deviation *ec*. The output variable is the frequency adjustment value *u* of the inverter. The corresponding fuzzy languages ​​are E, EC, and U, respectively. The range of the input and output variables is mapped to the interval [-3, 3] through a specific mapping rule, belonging to the fuzzy set {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, with 7 fuzzy subsets denoted as NB, NM, NS, ZE, PS, PM, and PB, respectively. The membership function adopts the commonly used triangular function. The fuzzy membership function editor in the fuzzy logic toolbox can be used to easily set each language variable and its membership function. Based on the technical knowledge and practical experience of the engineers and combined with the experimental results, a language control rule table is compiled, as shown in Table 1. The fuzzy control rules are input using the fuzzy rule library editor, and the weighting value of each rule is set to the default value of 1. The entire fuzzy inference process adopts the commonly used Max-Min method, and the defuzzification method is the centroid method. Table 1 Fuzzy Language Control Rules Table 3.3 Fuzzy Controller Testing and Simulation LabVIEW is a graphical development platform for virtual instruments. It provides a large number of input/output instrument panels, as well as various functions and signal generators, which can easily input and output various data and generate different analog signals. In addition, it also has various additional software packages, such as disk management, automatic testing, control and simulation, signal processing, graphics acquisition and processing, numerical analysis tools, etc., which can simulate real systems. The input/output performance testing function of the fuzzy logic controller design VI can also be used to test the fuzzy controller VI, intuitively observe whether the output obtained by different deviations and deviation change rates meets the requirements, verify whether the control rules are correct and reliable, and then modify and improve the fuzzy controller. After the test is completed, the data is saved in a data file with the .fc format. 3.4 System Implementation The designed fuzzy controller is loaded into the fuzzy controller VI and applied to the LabVIEW block diagram program. According to the functions required by the system, the corresponding instrument control front panel and background block diagram program are designed. Figure 2 shows the main block diagram program. The completed system features a user-friendly human-machine interface, displaying real-time pH and flow status visually via curves. It also includes functions such as querying historical data, storing large amounts of data, providing audible and visual alarms, and printing reports. Furthermore, the control interface can be published to the network using LabVIEW for remote monitoring. [align=center]Figure 2 System Program Flowchart[/align] 4. Conclusion The LabVIEW-based gray water fuzzy control system fully utilizes LabVIEW's openness and graphical programming methods, leveraging the robustness and dynamic response characteristics of fuzzy control. It has achieved good control results in practical applications. LabVIEW is a powerful virtual instrument development tool, providing a convenient and flexible platform for developing powerful and high-performance control systems. The fuzzy controller designed using the LabVIEW Fuzzy Logic Toolbox does not require establishing a mathematical model of the controlled object. It exhibits adaptability to the time delay, nonlinearity, and time-varying characteristics of the controlled object. Moreover, the design process is very convenient and quick, allowing for rapid application to various industrial process control and automation software developed based on LabVIEW, providing a new approach for the efficient development of fuzzy control systems. References [1] Xiao Bingyan. Application of fuzzy control mechanism in the treatment of ash flushing water in Baosteel power plant [J]. Baosteel Technology, 2002, 2: 44-46. [2] Fuzzy Logic for G Toolkit Reference Manual [EB]. National Instruments, 1997. [3] Zhang Jianmin, Wang Tao, Wang Zhongli, et al. Principles and Applications of Intelligent Control [M]. Beijing: Metallurgical Industry Press, 2003.