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This paper addresses the design of flight control system related to neural network-based adaptive dynamic surface control for the longitudinal motion of an airbreathing hypersonic vehicle. The control objective is to provide adaptive velocity and altitude tracking in the presence of the model uncertainties and unknown nonlinearities caused by changes of flight conditions. By approximating the unknown...
Air pressure in proton exchange membrane fuel cells (PEMFC) directly affects fuel cells' electrochemistry-reactivity performance. It not only related to air flow and air temperature, but also affected by PEMFC output power. In order to make it in a proper value, the paper designed air pressure servo control system which given value was predicted in advance by Elman ANN according to PEMFC output power,...
Aiming at forecasting failure time of the missile more accurately, saving the manpower, money and material resources, a data-fusion forecast model based on artificial neural network was put forward. First, several single forecasting methods including grey model, time series model and so on were used. Then, all of the single forecast results were fused by artificial neural network. The model was calculated...
Nitrogen oxide (NOx) is one of main pollutants emitted from coal fired power plants and is a significant pollutant source in the environment. Therefore, the monitoring or prediction of NOx emissions is an indispensable process in coal-fired power plant so as to control NOx emissions. In this paper, NOx emissions modeling for real-time operation and control of a 300MWe coal-fired power generation plant...
The purpose of this study is to investigate the data fitting for broiler growth performance parameters. In this paper, the gradual advancing analysis methods, from correlation analysis, multiple linear regression, to neural network, are proposed. The mean technology roadmap is: firstly, correlation analysis is used to detect the degree of correlation between the broiler growth performance parameter...
Unmanned Aerial Vehicle (UAV) is defined as aircraft without the onboard presence of pilots. UAVs have been used to perform intelligence, surveillance, and reconnaissance missions. The UAVs are not limited to military operations, they can also be used in commercial applications such as telecommunications, ground traffic control, search and rescue operations, crop monitoring, etc. In this paper, we...
Clustering techniques has been applied to the classification of industrial pollution source. Use the features of industrial waste water pollution sources and waste gas pollution sources to build the data model, and cluster about 30000 records of pollution sources, then assess and explain the clustering results. Build a two-dimensional classification based on waste water and waste gas according to...
It is difficult to establish accurate models for complex flight control systems, but neural network has arbitrary nonlinear approximation ability. In order to overcome modeling errors and disturbances, a method of hybrid flight control is proposed. Firstly, inverse model of the object is identified online through neural networks and the feedback linearization control system is reached. And then circle...
A novel nonlinear modelling approach has been developed and implemented on Alstom gasifier using Wiener model. The linear element of the Wiener model was identified by a combined subspace state space method, which integrated MOESP (Multivariable Output-Error State Space) and N4SID (Numerical algorithms for subspace state space system identification) method in the estimation of system matrices. Then...
An accurate estimated flight time is essential to modern air traffic management systems. Because the forecast is associated with many factors and needs large numbers of statistical calculation, the traditional methods used to forecast flight time are limited and inadequate. In this article, a back propagation neural network model is presented for forecasting the flight time. Firstly, the main factors...
Aimed at the bulky nonlinear temperature system with time-delay, a DFOPDT model is established. The relation between the classical model and the disperse model of the system is deduced. An algorithm is presented which is an effective way to solve unknown parameters of the model by neural network. The network can soon converge through the iterative calculation in which the value of unknown parameters...
The purpose of this study is to investigate the prediction models for broiler growth performance. In this paper, a multi-meteorological factors-based neural network model (MMFNN) is proposed. We discuss the meteorological factors selection and the construction of MMFNN in detail. The influences of both air temperature and relative humidity to the rate for sale is taken for example to evaluate our...
A neural network-based algorithm for retrieving precipitable water vapor (PWV) using the Advanced Very High Resolution Radiometer (AVHRR) data is proposed. The neural network (NN) model is combined with the radiative transfer calculations using MODTRAN 4.0 with the latest global assimilated data. The selected NN is a multilayer feed-forward neural network. The input variables are the top-of-atmosphere...
This paper attempts to research the issue of in-flight icing identification of aircraft flight dynamics. A nonlinear aircraft dynamics model is set up to simulate the wind turbulence effect on aircraft. The effect on flight dynamics by icing and wind disturbance are compared with clean one. In non-steady atmosphere, it becomes not so easily to detect. So a method using neural network and Kohonen self-organizing...
Land surface temperature (LST) is a key variable for studies of global or regional land surface processes, energy and water cycle, and thus, has important applications in various areas. Atmospheric correction is a major issue in LST retrieval using remote sensing data because the presence of the atmosphere always influences the radiation from the ground to the space sensor. Atmospheric correction...
A method based on neural networks is proposed to retrieve precipitable water vapor (IPWV) over land from brightness temperatures measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). Water vapor values provided by European Centre for Medium-Range Weather Forecasts (ECMWF) were used to train the network. The performance of the network was demonstrated by using an...
Global solar radiation is need knowledge for solar energy system design. In this work, the artificial neural networks (ANN) were applied to estimate the daily global solar radiation in China. Eight-year meteorological data from ten weather stations, which located at very different locations and climate zone, was randomly split into training, validation and test set with the proportion of 2:1:1. Daily...
Air supply flow directly affects proton exchange membrane fuel cells' (PEMFC) performance, when air supply flow exceeded PEMFC demands, lost of heat energy increased and power consumption of air-compressor increased too, so efficiency of generating current was reduced. Whereas, when air flow was under its demands, FC stack would be damaged with output power of PEMFC increasing in some extant. But...
This paper presents the identifications of ammonia concentration by using several different neural network (NN) models. The shear horizontal surface acoustic wave (SH-SAW) device coated with polyaniline (PANI) film was applied as ammonia sensor. The data sensed by SH-SAW sensor was implemented by these NN models. A reliable and superior intelligent identifier is expected to be found for effectively...
This paper researches the principle and method of the BP NN modeling, makes use of the BP NN built up the non-linear model of airplane DC dynamo. After the model is trained by the characteristic data of airplane DC dynamo, successfully gets the empty characteristic curve and the voltage-time curve of impact load and impact unload by voltage adjustor. The result proves that the model of airplane DC...
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