In order to realize intelligent greenhouse, an automatic navigation method for a mobile platform based on ultra-wideband (UWB) positioning technology was proposed and validated in this study. The time difference of arrival (TDOA) approach was used to monitor and track the UWB positioning to obtain the localization information of the mobile platform working in a greenhouse. After applying polynomial fitting for positioning error correction, the system accuracy was within 5 mm. A fuzzy controller model was constructed by incorporating the lateral and heading deviations as input variables and the steering angle of front wheel as the output variable. A fuzzy rule was established based on domain knowledge, as well as the steering angle of front wheel offline query table, which was applied to alleviate the calculative load of the controller. Experimental results confirmed that the automatic navigation method proposed in this study performed satisfactorily, with a steady-state error ranging from 41 mm to 79 mm when tracking straight line, and an average error of 185 mm and an average maximum error of 532 mm when tracking polygon. In addition, the maximum error occurred at the polygonal corner which could meet the needs of driving on the narrow road in the greenhouse. The method proposed in this study provides a new systematic approach for the research of greenhouse automatic navigation.
Reinforcement learning (RL) is a solution with great potential for hybrid electric vehicle (HEV) energy management strategies (EMS). However, traditional deep reinforcement learning (DRL) suffers from inefficiency and poor stability during random exploration in action space, so it is necessary to model some advanced driver experience knowledge and combine it with DRL. Herein, an advanced driver experience (DE) model of traffic congestion level and power matching is constructed based on fuzzy clustering and embedded into DRL. The results show that the DE embedding improves the training convergence efficiency of DRL on a power‐split HEV model, where it improves the convergence of the deep deterministic policy gradient (DDPG) by 46.2%. As DE can better adjust engine operating points and vehicle drive modes under various driving cycles, it enables DDPG to improve fuel economy by ≈6.29% while maintaining the terminal state of charge. This study aims to improve the efficiency of action space exploration and optimize the DRL learning strategy, so as to provide a theoretical basis for the design and development of EMS.
Because the safety factor of underground mining issues, we have designed an RFID-based underground personnel positioning system design, the system can be used in systems for daily attendance, reduce accidents in human factors, safety in the event of an accident, for accident investigation provide an important basis.
The development of computers wireless network monitoring system mainly includes steps such as the selection of transmission protocol, the calls of database program, data display and automation implementation and so on. The transmission speed of protocol TD-SCDMA is faster. In addition, it also can transmit voice and pure data files. Thus, this article selects TD-SCDMA protocol as transport protocol of wireless sensor networks. On the basis of the software OLEDB, this paper has developed ActiveX Data Object program, and has implemented the safety supervision automation process of wireless sensor network technology. Finally, this paper uses VC++ software to make a numerical simulation experiment on computer programs by taking an example of coal mine gas monitoring. At the same time, through the display on the window, it is the gas concentration monitoring curve that is obtained when the mine safety is abnormal, which provides the safeguard for mine personnel safety and normal work.
In this paper, the deformation behaviour of the large steel tank under uneven foundation settlement is investigated. The finite element model of the tank is firstly established, the finite element analysis of the large steel tank under the harmonic settlement conditions is carried out consequently, the influence of height-diameter ratio, diameter-thickness ratio and wind girder stiffness on the deformation behaviour of the tank top is studied. Based on the finite element results, regression equation for predicting maximum radial displacement of the tank is proposed. Furthermore, the accuracy of proposed solution is validated.
Based on the traffic analysis zones (TAZ) divided according to the type of land use, the trip generation volume of each TAZ can be calculated by using trip generation rates in land classification method, which urges us to find appropriate generation rates to ensure the reliability of the results. While OD matrix estimation method can acquire trip generation volume according to the volume of road sections with the drawback that this method requires to complete road traffic data and reasonable prior matrix. The paper combines the advantages of the two methods mentioned above. First, the trip generation volume of each TAZ is still calculated based on the generation rates, which can be used to calibrate the OD matrix estimation model. Once the OD matrix is estimated, the generation rates can be refined, and thus a new OD matrix can be computed. Then keep adjusting the data until it meets the accuracy demand. At last, a statistical test which can be used to judge the iteration will be presented.
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