Intelligent PID Control Algorithm Research Articles

Research on Intelligent Control System of Thermal Print Head Based on FPGA

Thermal print head heating realtime temperature fluctuations are too large, often causing damage to the print head heating point, resulting in poor print quality and unsatisfactory print results. Therefore, in order to improve the stability of the thermal print head during printing, and at the same time solve the inefficiency of the traditional single chip microcomputer control of the thermal print head heating method, a field programmable gate array (FPGA) based thermal print head heating control method is proposed. In order to control the core, the intelligent fuzzy PID control algorithm is used to ensure that the temperature of the print head can be stabilized quickly. Through simulation and experimental verification, it is shown that the intelligent fuzzy PID control algorithm greatly improves the temperature stabilization effect, and the time required to reach stability short, not only improve the printing accuracy, but also extend the life of the print head.

Aquiculture Remote Monitoring System Based on Android Platform

With the rapid development of modern science and technology, the application of the Internet and of technology in Intelligent Agriculture has become more and more widespread. In this paper, a kind of aquaculture remote monitoring system based on the Internet Android platform is introduced. Using the system with many sensor nodes, information (such as pH value, temperature, water level, dissolved oxygen and other environmental parameters) can be collected remotely by many kinds of sensors (such as a pH sensor, temperature sensor, water level sensor, and dissolved oxygen sensor), and then the analog data collected can be transformed to be digital data. The digital data can be sent to an Android mobile system by socket communication. In the Android mobile control interface the data received from pound can be exported into a SQLite database, and the data in the SQLite database can be exported into a SD card and stored in the format of TXT. The filename stored is formed with the information from the time when the TXT file is saved (such as year-month-data-hour-minute-second) in order to avoid the problem of having the file overwritten by a file with the same name file. Therefore, the user needs not designate the name of the saving TXT file. To the Android application, many control nodes can be controlled remotely. The system adopts CC2430 as the underlying management chip. Temperature measurement accuracy of the system can reach 0.5°C. In addition, pH measurement accuracy of the system can reach 0.3. A good control algorithm can achieve good control precision. In our system, in order to obtain more control precision, an intelligent fuzzy PID control algorithm is applied in the remote MCU control system. Dissolved oxygen is a very important parameter in aquiculture. In the system dissolved oxygen control precision can be controlled within ±0.3 mg/L. Moreover, the SOKCET communication is designed in an independent thread to the system. Thus, the reaction of the control system is very sensitive. The function of the system is not limited by time, regional, and climate conditions. The interface of the application is designed in the Android Mobile phone, so the user can handle the application flexibly and conveniently, and the user can browse data from the mobile phone, send remote control commands, and control the bottom water, pump water supply pump, and aerator in any location with an Internet connection. The IP address is exported into a SQLite database, so the IP data can be obtained automatically from the database by the system after the application is started, and it does not need input from the user repeatedly. Many mobile phone clients of the system can share a single server. Thus, the system has a very high price-performance ratio. After practical testing of the system, it has the advantages of simple operation, fully able to meet the need of aquaculture. c.

Cloud Neural Fuzzy PID Hybrid Integrated Algorithm of Flatness Control

In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neural network and fuzzy integration. By indeterminacy artificial intelligence, the problem of fixing the membership functions of input variables and fuzzy rules was solved in an actual fuzzy system and the nonlinear mapping between variables was implemented by neural network. The algorithm has the adaptive learning ability of neural network and the indeterminacy of a cloud model in processing knowledge, which makes the fuzzy system have more persuasion in the process of knowledge inference, realizing the online adaptive regulation of PID parameters and avoiding the defects of the traditional PID controller. Simulation results show that the algorithm is simple, fast and robust with good control performance and application value.

Research on Intelligent Synchronization Control of Erecting System Driven by Two Hydraulic Cylinders

The synchronization control problem of a large equipment erecting system driven by two oil cylinders side-by-side is analyzed. A closed loop control scheme of hydraulically driven erecting system based on electro-hydraulic proportion control valve is given. Considering the existence of time-varying parameters of hydraulic system, intelligent PID control algorithm is implemented by adding neurotic adaptive element control approach to improve the adaptive control capacity of the controller. Simulation results show that the intelligent PID control algorithm is more effective than conventional method for the erecting system synchronization control.

Development of intelligent system for a thermal analysis instrument

The key techniques for the intelligent analysis instrument developed are proposed. Based on the technique of virtual instrumentation, the intelligent PID control algorithm to control the temperature of thermal analysis instrument is described. The dynamic character and the robust performance of traditional PID controls are improved through the dynamic gain factor, temperature rate change factor, the forecast factor, and the temperature correction factor is introduced. Using the graphic development environment of LabVIEW, the design of system modularization and the graphic display are implemented. By means of multiple mathematical modules, intelligent data processing is realized.