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In this paper, the problem of adaptive control with disturbance attenuation is investigated for stochastic discrete-time nonlinear systems with Markovian jumping parameters and unknown system parameters. Using the proposed control law and the sufficient conditions, the closed-loop system achieved H∞ performance. As a practical example of the considered problem, an air-fuel ratio controller for a gas engine intended as an electric vehicle extender is designed based on the proposed adaptive disturbance attenuation control algorithm. The air-fuel ratio controller is validated via a numerical simulation under three working conditions. The results of the numerical simulation show that the air-fuel ratio can be regulated into a range around its desired value by the proposed adaptive disturbance attenuation controller and that the adaptive law can be tuned to a steady value. The control performance indices of the proposed adaptive disturbance attenuation controller are smaller than those of the open-loop controller, which means that the proposed adaptive disturbance attenuation controller achieves a greater control effect.

Due to high operating cost, limited coverage range, complex installation and additional weight, helicopter and other general aviation aircraft may not have datalink function implemented as portion of its avionics system. However, datalink has great advantages of releasing crowed VHF channel resources, reducing pilot and controller workload, supporting automation application, gaining time efficiency and operation precision. During the preflight, in-the-air and post-flight periods, general aviation operators and ground stations always demand data from helicopters, similar to Airline Operation Control (AOC) for air transportation. The automotive control trends and mandatory standards also drive the installation of data communication for the helicopters. By using SysML modeling language, this paper tries to identify the data link communication scenarios and requirements for helicopters. The feasibility of utilizing existing high speed mobile network for helicopters data communication is analyzed and confirmed, which removes the cost obstacles of helicopter datalink applications. Based on the operational concept and requirement analysis, flexible and scalable datalink system architecture for helicopters is proposed, which support both the VHF ACARS and mobile cellular network. Since the weight and size of airborne system for helicopter is severely restricted, besides the data communication radios, all the other router, protocol stacks and applications should be hosted in the modular computing resources and/or multi-function displays. With an integrated data communication radio and the datalink partition hosted applications, the airborne datalink system can support the 4G/LTE, WiFi, VHF ACARS and other future new communication channels, e.g. broadband satellite communication and AeroMACS system etc.

This research aims to obtain the piston ring tribological characteristics of a free-piston engine. Mathematical models of piston ring seal and lubrication were established based on thermodynamic equation and hydrodynamic lubrication equation. The lubrication performances of the piston ring were simulated; the effects of the piston motion to piston ring lubrication process were analyzed compared with a corresponding conventional engine. Results show that seal working time of free-piston ring is longer than conventional engine's during a cycle time, but the leakage loss is lower. Besides, the oil film thickness of piston ring in free-piston engine is thinner than that of crankshaft engine just around TDC, but other position is thicker. Moreover friction forces and friction work of piston ring in two engines are almost equivalent, but the peak friction power of free-piston engine is larger than crankshaft engine.

Identification of apple stem-ends and calyxes from defects on process grading lines is a challenging task due to the complexity of the process. An in-line detection of the apple defect is developed in this article. Firstly, a computer controlled system using three color cameras is placed on the line. In this system, the apples placed on rollers are rotating while moving, and each camera is capturing three images from each apple. In total nine images are obtained for each apple allowing the total surface to be scanned. Secondly, the apple image is segmented from the black background by multi-threshold methods. The defects, including the stem-ends and calyxes, called regions of interest (ROIs), are segmented and counted in each of the nine images. Thirdly, since a calyx and stem-end cannot appear at the same image, an apple is defective if any one of the nine images has two or more ROIs. There are no complex imaging processes or pattern recognition algorithms in this method, because it is only necessary to know how many ROIs are there in a given apple's image. Good separation between normal and defective apples was obtained. The classification error of unjustified acceptance of blemished apples reduced from 21.8% for a single camera to 4.2% for the three camera system, at the expense of rejecting a higher proportion of good apples. Averaged over false positive and false negative, the classification error reduced from 15 to 11%. The disadvantage of this method is that it could not distinguish different defect types. Defects such as bruising, scab, fungal growth, and disease, are treated as the same.

This paper presents a system for apple color grading into four classes according to standards stipulated in China. To automatically grade apple fruit color, a laboratory machine vision system was developed, which consisted of a color CCD camera equipped with an image grab device, a bi-cone roller device controlled by a stepping motor, and a lighting source. Four images, one for every rotation of 90^o, were taken from each apple. Seventeen color feature parameters (FP) were extracted from each apple in the image processing. Three hundred and eighteen ''Fuji'' apples were examined by the system, and were divided into two sets, with 200 in ''Training set'' and 118 in ''Test set''. A method called organization feature parameter (OFP), based on formulae expression trees by using genetic algorithms (GA), was used in this paper. When the initial FP could not sensitively distinguish among different classes of apples, the FP were organized into one new OFP by using genetic algorithm. By applying the step decision tree algorithm in combination with the OFP method, high grade judgment ratios were achieved in the classification of two of four apple color grades, i.e., 'Extra', and 'Reject'. However, the grade judgment ratio for 'class I' and 'class II' was relatively low. Compared with BP-ANN and SVM, the OFPs method was more accurate than BP-ANN, but a little lower than SVM for identification results.

The measurement and calibration of the laser diffuse reflection characteristic from target is crucial for the evaluation of laser system.A target laser diffuse reflectance test system consisting of a large-diameter laser energy analyzer is described.The structure of this system ensures that the CCD observation system and 1.57 μm laser detector have the same optical axis.The CCD observation system and laser energy meter have same mechanism.With calibration results and experiment results,it is shown that the accuracy of laser diffuse reflection from target is high,and the test method is operationally excellent.

The indispensable role of Management Information Systems is common sense in the buisness and organizaiton circle. The use of Management Information Systems has gone from competitive advantage for few to business necessity for all. Its true value comes in empowering business competitiveness advantages by enhancing the organization's efficiency and effectiveness. Understanding the industry's booming environment and designing the best strategies to meet objectives is vital to expand business in the short and long run.

Knowledge management is seen by many to be a prerequisite for the successful organization. As a multidisciplined approach to achieving organizational objectives by making the best use of knowledge, its gaining value had been recognized by more organizations and adopted to leverage business efficiency and effectiveness. Exploring the importance of knowledge management in the new businesis enviroemnt s of great necessity and therefore will bring significent evolution to the operation.

More than 3.2 million litres of vinegar is consumed every day in China. There are many types of vinegar in China. How to control the quality of vinegar is problem. Near infrared spectroscopy (NIR) transmission technique was applied to achieve this purpose. Ninety-five vinegar samples from 14 origins covering 11 provinces in China were collected. They were classified into mature vinegar, aromatic vinegar, rice vinegar, fruit vinegar, and white vinegar. Fruit vinegar and white vinegar were separated from the other traditional categories in the two-dimension principal component space of NIR after principle component analysis (PCA). Least-squares support vector machine (LS-SVM) as the pattern recognition was firstly applied to identify mature vinegar, aromatic vinegar, rice vinegar in this study. The top two principal components (PCs) were extracted as the input of LS-SVM classifiers by principal component analysis (PCA). The best experimental results were obtained using the radial basis function (RBF) LS-SVM classifier with σ = 0.8. The accuracies of identification were more than 85% for three traditional vinegar categories. Compared with the back propagation artificial neural network (BP-ANN) approach, LS-SVM algorithm showed its excellent generalisation for identification results. As total acid content (TAC) is highly connecting with the quality of vinegar, NIR was used to prediction the TAC of samples. LS-SVM was applied to building the TAC prediction model based on spectral transmission rate. Compared with partial least-square (PLS) model, LS-SVM model gave better precision and accuracy in predicting TAC. The determination coefficient for prediction ( R p ) of the LS-SVM model was 0.919 and root mean square error for prediction (RMSEP) was 0.3226. This work demonstrated that near infrared spectroscopy technique coupled with LS-SVM could be used as a quality control method for vinegar.

Apple is a very important fruit in China. The shape of the apple is important indices for classifications. An image collecting system was developed and 4 images are obtained from each apple in this study. In order to describing the irregular shapes of apples, Fourier expansion was developed to reduce the dimensionality of the edge points of an image to a set of 33 Fourier coefficients. These coefficients and variables were used as feature parameters. A new method called organization feature parameter based on formulae expression tree by using genetic algorithm was proposed in this paper. It could solve the problem how to getting optimum feature parameters. By applying "step decision tree" descriptor in combination with the new method to identify the shape of apples, the grade judgment ratios for "extra", "categories II" and "reject" are high, but the ratio for " category I" is not high.