An intelligent model is developed to predict the surface roughness of aluminium alloy in the milling operation based on least square support vector machine (LS-SVM). The Taguchi’s design of experiment was adopted to ...
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An intelligent model is developed to predict the surface roughness of aluminium alloy in the milling operation based on least square support vector machine (LS-SVM). The Taguchi’s design of experiment was adopted to provide enough training information with minimal experiment times. The present prediction model is to analyze the effects of condition factors, such as spindle speed, feed rate, etc. on the surface roughness (Ra). The tests have been conducted to verify the LS-SVM model, and the average prediction error is about 8%. It means the model is capable to predict the surface roughness well.
This paper deals with a positioning speed and precision control system for the assembly of segments of a shield tunneling machine. First, we design a six degrees of freedom segment erector with electrohydraulic drive....
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This paper deals with a positioning speed and precision control system for the assembly of segments of a shield tunneling machine. First, we design a six degrees of freedom segment erector with electrohydraulic drive. Then, the segment positioning process and the dynamics model of the electrohydraulic system are analyzed theoretically. Segment positioning control system is designed, making comparisons between speed and displacement/angle control in terms of efficiency and precision. Several reference speed run curves are selected to control the segment positioning process. Simulations are carried out to achieve the selected optimal run speed of the segment. The simulation results verify the validity of the proposed control system.
Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is...
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ISBN:
(纸本)9789746724913
Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.
This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stocha...
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This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.
In this paper, a new procedure for implicit surface reconstruction from oriented points is presented. A normal constraints based implicit polynomials fitting method and the partition of unity approach are fused into o...
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A novel coefficient modeling for skewed PM and overhang structure as a coefficient estimation method is introduced for optimal design in the 2D region for a PM motor. The novel model is constructed using 3D FEM and a ...
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To define which detect electrode type between two elecrodes and three elecrodes can extend the operating range of capacitance proximity fuze, took sphere as elecrode, and equivalent sphere models of two and three elec...
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To define which detect electrode type between two elecrodes and three elecrodes can extend the operating range of capacitance proximity fuze, took sphere as elecrode, and equivalent sphere models of two and three elecrodes were established. The mirror method and Ansoft Maxwell microsoft were used to calculate the capacitance value of the model, then got the figure of capacitance-missile target distance. Based on this, Matlab was used to calculate the oscillator frequency, and got the fiure of frequency-missile target distance. According to the capacitance value and oscillator frequency, got the figure of capacitance changes-missile target distance and the figure of frequency changes- missile target distance. By comparing the frequency changes of the two electrodes with the changes of the three electrodes, draw the conclusion that the changes of three electrodes type are bigger than the ones of two electrodes type, so three electrodes type is better than the the two electrodes type to extend the operating range.
Electrical capacitance tomography (ECT) has been developed for two decades to visualize the internal behavior of industrial processes containing dielectric components. Three different ECT systems have been developed: ...
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Electrical capacitance tomography (ECT) has been developed for two decades to visualize the internal behavior of industrial processes containing dielectric components. Three different ECT systems have been developed: (1) based on a charge/discharge capacitance measuring circuit, (2) based on an AC circuit and (3) based on an impedance analyzer. In this paper the operation principles, calibration methods and some performance of the three systems are compared. The experimental results prove that the AC-based ECT system is superior to the charge/discharge ECT system. Although the impedance analyzer based ECT system can provide the highest accuracy and the best image quality, it is bulky and expensive.
The identification problem of multivariable output error systems is considered in this paper. By constructing an auxiliary model using available input-output data and by replacing the unknown inner variables in the in...
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The identification problem of multivariable output error systems is considered in this paper. By constructing an auxiliary model using available input-output data and by replacing the unknown inner variables in the information vector with the outputs of the auxiliary model, an auxiliary model-based stochastic gradient (AM-SG) identification algorithm is presented. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates given by the AM-SG algorithm converge to their true values. The AM-SG algorithm with a forgetting factor is given to improve its convergence rate. The simulation results confirm the theoretical findings.
Inattentive and impaired drivers are a major cause of road accidents. Especially when impaired by drugs, fatigue or physical handicaps, the skill levels, driving habits, capabilities and decisions of a human driver ar...
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Inattentive and impaired drivers are a major cause of road accidents. Especially when impaired by drugs, fatigue or physical handicaps, the skill levels, driving habits, capabilities and decisions of a human driver are adversely affected. In such cases, the ability of a driver to safely operate a vehicle may be augmented considerably by well tuned and driver adaptive warning and assistance systems. Data from 105 drivers were collected in the Drive Safe project on an approximately 30 km route containing both city and highway traffic. The data was used to develop methods for determining inattentive/impaired drivers. This paper is on a lane keeping driver assistant system that is activated once such an inattentive/impaired driver who cannot perform a good task of lane keeping by himself is determined. Robust, parameter space based and velocity scheduled control design techniques carried out in the COMES toolbox are used for designing the lane keeping controller. A camera based image processing algorithm for lane detection and tracking is used. The image processing algorithm and the lane keeping assistant control system are evaluated first using offline simulations and then using more realistic, real time hardware-in-the-loop simulations. While a relatively simple linear model is used for lane keeping controller design, evaluation of the designed controller also uses the high fidelity, high order, realistic and nonlinear vehicle model in Carmaker HiL. A PC is used for processing video frames coming from an in-vehicle camera pointed towards the road ahead. Lane detection and tracking computations including fitting of composite Bezier curves to curved lanes are carried out in this PC. A dSpace microautobox is available for obtaining the lane data from the PC and the Carmaker vehicle data from the dSpace compact simulator used and calculating the required steering actions and sending them to the Carmaker vehicle model. Offline and real time simulation results demonstrate t
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