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Application of Neuro-Fuzzy Controller to Autonomous Agricultural Vehicle Operating on Unstructured Changing Terrain -Control Software Development-

机译:模糊控制器在非结构化变地自主农用车辆上的应用-控制软件开发-

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摘要

The control of an autonomous agricultural vehicle operating on unstructured changing terrain includes many objective diffi culties. One major diffi culty concerns the characteristics of the terrain condition that the vehicle should operate in. Problems ranged from the effects of varying terrain conditions on the autonomous vehicle sensors and traction performance through to the need to deal with the presence of unexpected situations. On unstructured changing terrain, many factors infl uence vehicle behavior such as terrain slope, lateral slippage, and so on. Therefore, it is necessary to develop a more suitable model for vehicle motion on these terrain conditions. In order to control the vehicle along a course on unstructured changing terrain, it was developed control software to enable more accurate control. The developed method to control the vehicle when operating on these conditions was Neuro-Fuzzy Controller. Result of the trained model could be described as follows; number of nodes was 193, number of fuzzy rules was 81, average testing error between simulation and ANFIS output was 0.76, while for experimental and ANFIS output was 1.61. It was concluded that the developed control system had a good accuracy to steer the vehicle.
机译:在非结构化的不断变化的地形上运行的自动农用车辆的控制包括许多客观难度。一个主要的难题涉及车辆应在其上行驶的地形条件的特征。问题的范围从变化的地形条件对自动驾驶车辆传感器和牵引性能的影响一直到需要应对意外情况的存在。在非结构化的不断变化的地形上,许多因素会影响车辆的行为,例如地形坡度,侧向滑移等。因此,有必要针对这些地形条件下的车辆运动开发更合适的模型。为了在非结构化的不断变化的地形上沿路线控制车辆,开发了控制软件以实现更精确的控制。在这些条件下操作时,用于控制车辆的已开发方法是Neuro-Fuzzy Controller。训练模型的结果可以描述如下:节点数为193,模糊规则数为81,模拟与ANFIS输出之间的平均测试误差为0.76,而实验和ANFIS输出之间的平均测试误差为1.61。结论是,开发的控制系统具有良好的操纵车辆的准确性。

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