Dong Sheng, Yuan Zhaohui, Gu Chao, Yang Fang. Research on intelligent agricultural machinery control platform based on multi-discipline technology integration[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(8): 1-11. DOI: 10.11975/j.issn.1002-6819.2017.08.001
    Citation: Dong Sheng, Yuan Zhaohui, Gu Chao, Yang Fang. Research on intelligent agricultural machinery control platform based on multi-discipline technology integration[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(8): 1-11. DOI: 10.11975/j.issn.1002-6819.2017.08.001

    Research on intelligent agricultural machinery control platform based on multi-discipline technology integration

    • Abstract: The meaning of agricultural machinery automation and intellectualization includes a wide range of content, involving a large number of engineering disciplines, such as navigation, images, models and strategies, actuators and data chain. The intellectualization of agricultural machinery is the symbol of a country's engineering and technical strength. How to co-ordinate the multidisciplinary technologies and reasonably integrate them into a system is the key to the success of intelligent agricultural machinery. According to the requirements of the development of land scale management in China, intelligent agricultural machinery should use advanced technology in the aeronautics, astronautics and ground to achieve high-speed computing and transmission of data information in a dynamic environment, and to command the actuator to complete the tasks efficiently and effectively. In recent years, the research on intelligent agricultural machinery has been mainly concentrated on vision measuring, image processing, trajectory tracking and vehicle navigation, pattern recognition and their application, and so on, which have focused on image information acquisition method, image processing and recognizing algorithm, intelligent navigation algorithm and system integration application, and so on. The technology of automatic steering control, obstacle detection and active obstacle avoidance, and multi machine cooperative navigation, and the technology of agricultural machinery will be the focus of the next generation of intelligent agricultural machinery. This paper studied the Beidou enhanced network and network RTK (real-time kinematic) method to improve the accuracy of positioning and navigation technology, accurately modeled and compensated aiming at the inertial navigation error of agricultural machinery, and prolonged the working time of positioning. The dynamic model of agricultural machinery was established, and the parameters of the model were identified on the basis of the actual situation. Based on the constraint conditions, the knowledge learning and decision control technology was introduced into the agricultural machinery. And then combined with machine vision, the perception of the working environment and operating objects was enhanced, and the image recognition algorithm was used to assist navigation and control. Finally, according to the requirements of remote monitoring, and navigation and positioning for data transmission, the realization of data transmission technology of three-dimensional topology was studied so as to ensure the real-time data fusion of various technical units. The invention disclosed a set of intelligent device with electromechanical integration. It was equipped with a multi-source fusion intelligent controller based on the dynamic model of agricultural machinery, and an inertial navigation system, which could effectively isolate the disturbance of agricultural machinery to achieve stable tracking and the combination of WIFI and the new generation of Internet of Things to complete the multi-link data communication. According to the dynamic analysis of agricultural machinery, the data model was obtained. The model structure was determined, but the parameters were uncertain. The model parameters could be obtained by on-line identification on the basis of the minimum value of the difference between the actual state and the model state. Then the control strategy was designed according to the model. Based on the navigation control error prediction, the control law parameters were optimized through minimizing the objective function of the future control deviation, and the trajectory tracking of agricultural machinery would be always controlled with the best control parameters. Agricultural navigation used the tight integrated navigation technology of Beidou plus IMU (inertial measurement unit), and machine vision was taken as an aid. Based on the enhanced technology of mobile network base station of Beidou Foundation and high precision standard inertial navigation system for precision agriculture applications, the continuity and reliability of navigation and positioning information were ensured, which laid the foundation for the use of intelligent agricultural machinery in remote sensing areas. Therefore, the agricultural machinery in the next period will be more intelligent and easy in operation. New farmers in the Farm Hall will command all kinds of agricultural machines to carry out operations in a variety of environmental conditions, and monitor agricultural machinery in a few kilometers or tens of kilometers away in real time, which greatly reduce the burden on farmers, and achieve high efficiency, standardization and hommization, and also provide some technical references for the development of other industries.
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