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GAO Xu, E-mail: 2452052464@qq.com
Outline
Aiming at the problems of low tracking accuracy and poor scene adaptability of the existing differential tracked chassis path tracking controller, this study uses a small light and simple tracked cabbage harvester as a test platform to innovatively design an improved particle swarm optimization (IPSO) with fore-look distance adaptive fuzzy pure tracking controller (IPSO-FUZZY-PP). First, the study analyzes the operating characteristics of the cabbage harvester's pulling roller, and the cabbage's demand for navigation accuracy is determined. Then, the differential kinematics model of the crawler harvester is constructed to clarify the relationship between the track speed on both sides and the driving and steering states. The lateral deviation and heading deviation are used as the input of the fuzzy controller, and the PWM duty cycle difference of the two-sided motor is used as the output. The IPSO algorithm is used to dynamically optimize the fore-look distance. The simulation results show that the convergence speed of the controller is 60% higher than that of the traditional particle swarm optimization algorithm, which can effectively avoid the local optimal solution. In the cement pavement test (driving speed of 0.5 m/s), the maximum tracking deviation of the controller is 0.035 m, and the average absolute deviation is 0.017 m. Compared with the traditional pure tracking controller, the accuracy is improved by 34.6%, the rise time is shortened from 1.71 s to 0.76 s, and the response speed is improved by 55.6%. In the field test (driving speed 0.3, 0.5, 0.8 m/s), the maximum tracking deviation is not more than 0.031 m, 0.037 m, 0.041 m, respectively, and the average absolute deviation is controlled within 0.010 m, 0.015 m, 0.018 m, respectively. Compared with the traditional pure tracking controller, the accuracy is improved. The controller proposed in this study can dynamically adapt to the narrow row spacing and multi-speed conditions of cabbage harvest, meet the accuracy requirements of cabbage harvest navigation, and provide technical support for the precise alignment of unmanned cabbage harvest.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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