Intelligent Control System Research Of Combine Load Feedback

With the rapid development of microelectronics and computer technology, monitoring and automatic control technology has been widely used in modern agricultural machinery. Combine is one of the main equipments of modern agricultural machinery. The forward speed of combine is an important factor in productivity and work quality of combine. Domestic and foreign related studies show that it can improve the work quality and reduce the failure rate, which can maintain a constant palstance of threshing cylinder through the control of forward speed of combine. According to the characteristic of complexity and time delay, it is not easy to establish a precise mathematical model, so control of threshing cylinder is difficulty. The introduction of embedded technology and intelligent control technology to realize the intelligent control of the combine operation, it is not only the key to improve the production efficiency and threshing quality, but it also has great significance for the entire agricultural production.The object of study is the stripping combine harvester 4LZ-2.0.Embedded technology and fuzzy neural network intelligent control algorithm are used to build a intelligent control systems of combine harvester load feedback. Specific contents include the following aspects:1. Combine cylinder power consumption model: According to the analysis and research of threshing cylinder, this study establishes a more accurately mathematical model of threshing cylinder, which reflects the characteristics of threshing cylinder.2. Control system design of combine load feedback: According to the study of the working principle and structure characteristics of combine harvester 4LZ-2.0, control strategy and structure of control system hardware and software are proposed.3. Design of fuzzy neural network controller: This study mainly discusses the basic principles of artificial neural network and integration approach of fuzzy systems and neural network, and details principle, structure, algorithms of fuzzy neural networks.Finally, this study make simulation of cylinder power consumption model and fuzzy neural network controller by Simulink. Stripping combine harvester 4LZ-2.0 is used during the experiment in the field, which proves that the control system has certain stability and can reach anticipated effects.