关键词：
Active vibration control;frequency domain;least mean square method;flexible manipulator;fast Fourier transform;inverse fast Fourier transform;pump truck
摘要：
This paper aims to reduce the tip vibration of an ultra-long flexible manipulator subjected to impact loads. A modified least mean square method is proposed to determine the frequency response matrix of control paths and identify the complex amplitude of external excitation responses. The presented work is innovative in the sense that: (1) a theoretical model and a new algorithm are proposed for the identification of explicit convergence conditions of online parameters, and they are used to calculate output variables for the optimized robotic control; (2) an active numerical approach is developed to control the response of the tip vibration of the manipulator. The control algorithm is based on a relational model of control parameters and system outcomes; (3) design of experiments is performed for the verification purpose. The active vibration control has been demonstrated on a pump truck product where the third boom hydraulic cylinder is selected as the actuator for testing, and the manipulator tip is equipped with an acceleration sensor to collect the information of vibration; and (4) the performance of the proposed active vibration control has been validated on the flexible manipulator, and the results have shown that the amplitude of the vibration of robotic tip has been decreased for more than 60%.
期刊：
Advances in Transportation Studies,2019年1(Special Issue):49-60 ISSN：1824-5463
通讯作者：
Li, S.M.(lisumin57@gmail.com)
作者机构：
[Wei, J.; Zhao, L.; Liu, H.M.] School of Geosciences and Info-Physics, Central South University, Changsha;410083, China;[Li, S.M.] School of Architecture, Changsha University of Science and Technology, Changsha;610059, China;[Zhang, Z.S.] College of Basic Education, National University of Defense Technology, Changsha
通讯机构：
[Li, S.M.] S;School of Architecture, Changsha University of Science and Technology, Changsha, China
关键词：
Based on fuzzy theory;Emergency evacuation;Path optimization;Traffic hub
摘要：
Car-following is an essential trajectory control strategy for the autonomous vehicle, which not only improves traffic efficiency, but also reduces fuel consumption and emissions. However, the prediction of lane change intentions in adjacent lanes is problematic, and will significantly affect the car-following control of the autonomous vehicle, especially when the vehicle changing lanes is only a connected unintelligent vehicle without expensive and accurate sensors. Autonomous vehicles suffer from adjacent vehicles' abrupt lane changes, which may reduce ride comfort and increase energy consumption, and even lead to a collision. A machine learning-based lane change intention prediction and real time autonomous vehicle controller is proposed to respond to this problem. First, an interval-based support vector machine is designed to predict the vehicles' lane change intention utilizing limited low-level vehicle status through vehicle-to-vehicle communication. Then, a conditional artificial potential field method is used to design the car-following controller by incorporating the lane-change intentions of the vehicle. Experimental results reveal that the proposed method can estimate a vehicle's lane change intention more accurately. The autonomous vehicle avoids collisions with a lane-changing connected unintelligent vehicle with reliable safety and favorable dynamic performance.
摘要：
One-way roads have potential for improving vehicle speed and reducing traffic delay. Suffering from dense road network, most of adjacent intersections' distance on one-way roads becomes relatively close, which makes isolated control of intersections inefficient in this scene. Thus, it is significant to develop coordinated control of multiple intersection signals on the one-way roads. This paper proposes a signal coordination control method that is suitable for one-way arterial roads. This method uses the cooperation technology of the vehicle infrastructure to collect intersection traffic information and share information among the intersections. Adaptive signal control system is adopted for each intersection in the coordination system, and the green light time is adjusted in real time based on the number of vehicles in queue. The offset and clearance time can be calculated according to the real-time traffic volume. The proposed method was verified with simulation results by VISSiM traffic simulation software. The results compared with other methods show that the coordinated control method proposed in this paper can effectively reduce the average delay of vehicles on the arterial roads and improve the traffic efficiency.
摘要：
As China's urbanization process continues to advance and deepen, the spatial structure within each city is changing constantly.Analyzing the hidden relationship between human and land behind the massive urban data is a hot topic. In this paper, we apply the idea of network embedding to urban geography. The high-dimensional urban human activity data is embedded into the low-dimensional space (feature space) using the node2vec method. Compared to the traditional method of directly using high dimensional data analysis, node2vec can better detect the spatial relationship and structure of the network which are important for us to understand the urban functional areas more clearly. Based on Shanghai taxi data and subway travel data, we focused on the distribution and characteristics of functional areas in Shanghai .Then we verified the feasibility and superiority of node2vec.
摘要：
With the advancement and development of urbanization in China, human activities are closely related to the changes in the internal structure and external layout of the city. The human migration model reflects the internal structure of the city to some extent. In two places where the city is far apart, the layout is very similar, and people's activities may also have certain similarities. Inspired by Graphwave, the city's spatial network was constructed using data from human travel. It was found that the city's more important and potentially influential areas of urban functioning. This paper uses the data of Shanghai Mobike and taxis to build a network, identifies the similarity nodes in the city, uses the POI data set to verify the final data, and explains its important geographical significance. Experiments show that similarity nodes are mostly distributed in schools and communities, and are relatively close to transportation hubs.
摘要：
Nanoparticles are extensively used in various fields because of its surface and quantum size effects. Therefore, the measurement of nanoparticle size is of great significance to the development of nanotechnology. In order to accurately measure nanoparticles, dynamic light scattering particle technology can be used. However, it needs to solve the integral equation during measurement. In order to solve this problem, regularization inversion algorithm is proposed and designed a particle measurement system in this paper. The experimental results show that the inversion algorithm can accurately measure the particle size of nanoparticles and provide a reference for the development of dynamic light scattering particle technology.
摘要：
Mobile crowd sensing has become an emerging computing and sensing paradigm that recruits ordinary participants to perform sensing tasks. With the highly dynamic mobility pattern and the abundance of on-board resources, vehicles have been increasingly recruited to participate large-scale crowd sensing applications such as urban sensing. However, existing participant recruitment algorithms take a long time in recruitment decision for large number of vehicular participants. In this paper, a fast algorithm for vehicle participant recruitment problem is proposed, which achieves linear-time complexity at the sacrifice of a slightly lower sensing quality. The participant recruitment problem is modeled as a unconstrained maximization problem without explicitly cost constraint and a trade-off parameter is introduced to control the recruiter cost. Trace-driven simulations on both real world and synthetic data-sets are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed algorithm is 50 times faster than the state-of-art algorithm at the sacrifice of 5% lower sensing quality when the number of participants is over 1000. (C) 2017 Elsevier B.V. All rights reserved.
