Yueming Hu

Modeling and motion planning of a three-link wheeled mobile manipulator

This work set up the kinematics and dynamics modeling of three-link mobile manipulator by using Lagrange dynamics equation and nonholonomic dynamics Routh equation, and the method of artificial potential field was used to drive the mobile manipulator to finish the motion planning. The results of simulation illustrated correctness of the modeling and effectiveness of the method.

From Models to Code: Automatic Development Process for Embedded Control System

Current development method for embedded control system is mainly based on manual programming, so it is very time-consuming and is difficult to guarantee system performance. The paper presents a modeling language for embedded control system development, called ECSML, and a corresponding automatic code generation framework. ECSML satisfies the modeling requirements, including functionality and real-time performance, for control system. Based on ECSML, a graphical modeling environment has been created. The code generation framework takes advantage of the reusability of component-based development (CBD) method. A well-defined code structure, in which function code and non-function code are separated completely, makes it possible to generate all system code from models. This development method can promote development efficiency, reduce development cost and shorten the time to market of embedded control products.

Neural Network Modeling of Vehicle Gross Emitter Prediction Based on Remote Sensing Data

Vehicle emissions are a significant source of air pollution in cities. A neural network model for vehicle gross emitter prediction was established based on remote sensing data. The states of vehicle emission remote sensing system in China were described first, followed by a brief introduction to idle testing and remote sensing testing. After data collection, the choices in the algorithm and architecture, as well as original data were then analyzed and compared. The back-propagation (BP) neural network model with 7-20-1 architecture was also selected as the optimal approach with satisfied prediction. Compared with traditional model, the proposed approach has better accuracy and generality. The 81.63% correct results show the potentiality and validity of remote sensing for gross emitter prediction by using the neural network

Analysis of Vehicle Emissions and Prediction of Gross Emitter using Remote Sensing Data

Interest has focused on the analysis of vehicle emission based on the remote sensing data during the last two decades. This paper proposes an artificial neural network model for predicting taxi gross emitters using remote sensing data. Firstly, it introduces the field test in Guangzhou, and then analyzes the various factors from the emission data. Secondly, after doing principal components analysis and selecting algorithm and architecture, the back-propagation neural network model with 8-17-1 architecture was established as the optimal approach. It gives a percentage of hits of 93%. Finally, comparison among our former research results and aggression analysis results were presented. The results show the potentiality and validity of the proposed method in the prediction of taxi gross emitters

Optimal Path Planning for Autonomous Airship Based on Clonal Selection and Direct Collocation Algorithm

A novel algorithm, based on clonal selection and direct collocation theories, is introduced to solve the three-dimensional optimal path problem of airship. Firstly, the six-DOF (Degree of Freedom) nonlinear dynamic model for a special kind of airship is presented. Then, the model of novel algorithm is designed from clonal selection and direct collocation aspects respectively, and the dissipative energy function of airship is designed as performance index function. So the optimal control problem has been converted into the nonlinear programming problem which must subject to constraint conditions and performance index. Finally, nonlinear programming problem is solved by presented algorithm, and gets satisfied solutions. Simulation results also demonstrate the validity and feasibility of the presented novel algorithm for solving the optimal path problem of airship.

Modeling of Vehicle Gross Emitter Prediction Based on Remote Sensing Data

Vehicle emission is a major source of air pollution in urban cities. After the introduction of vehicle emissions remote sensing technology, the neural network model for high emitter prediction is made based on the 2004 remote sensing data of Guangzhou. The results show that satisfactory prediction was obtained by reasonable selection of original data for input layer element and algorithm. And the correct rate and the ability of generalization are superior to the traditional model in prediction.