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Anti-windup saturation compensation schemes in two-link flexible arms are studied. The singular perturbation approach is used to decompose the nonlinear system into a rigid subsystem and a fast subsystem, which allows a composite control design for the original system. A neural network is designed to compensate the saturation nonlinear in rigid subsystem, and a robust controller is employed to attenuate...
Data mining is a technology in data analysis with rising application in sports. Basketball is one of most popular sports. Due to its dynamics, a large number of events happen during a game. Basketball statisticians have task to note as many of these events as possible, in order to provide their analysis. In this paper, we used data from the First B basketball league for men in Serbia, for seasons...
Because traditional approaches for solving the simultaneous localization and map building (SLAM) problem have the limitation of computational complexity, imprecision of filter algorithm and fragile data association, soft computing technique has been used to solve the problem. In this paper, we reviewed the state of the art of the application of evolutionary algorithm, fuzzy logic and neural networks...
A new fault diagnosis system is proposed to recognize the faults of gear box in this paper by using the NMF-based characteristics extracting method and the neural networks technique. The results show that this method is effective for the fault diagnosis of gear box.
In this paper we analyzed the restriction factor of the stack crane speed, and put forward the adaptive control method of variable speed for stacker. Using the method of neural network we established the relationship between the highest permitted speed and carrying weight, carrying height of stacker. Finally we designed the control system of stacker based on neural network. It is improved that this...
Data mining technique is an effective tool used to obtain desired knowledge from massive data. Neural network is a new method in the application of data mining. Although it may have shortcomings of complex structure, long training time and uneasily understandable representation of results, neural network has high accuracy which is superior to other methods and this makes it more available in data...
The stator flux observer is a key part in the method of Direct Torque Control (DTC). However, the accuracy of the stator flux estimation directly affected the performance of DTC. The traditional induction motor stator flux observation method have been analyzed in This paper. And for the Shortcomings of existing methods, a on-line identification methods based on Radial Basis Function(RBF) have been...
In this research, the combination of modal data is used to identify the damage of a FEM model using neural networks. The identification ability with different levels of noise and incomplete mode shapes are also investigated. It has been proved that the neural network using combination of modal parameters as input has a excellent identification ability with ideal error tolerance and robustness. Numberical...
Neutralizing pH value of sugar cane juice is the important craft in the control process in the clarifying process of sugar cane juice, which is the important factor to influence output and the quality of white sugar. On the one hand, it is an important content to control the neutralized pH value within a required range, which has the vital significance for acquiring high quality purified juice, reducing...
The importance of symbolic analysis in the neural network approach to analog circuit fault diagnosis is discussed in this paper. Theoretical explanations and two explicative examples are presented, by taking into account the k-fault hypothesis.
In this work, design of low-voltage low-power analog artificial neural network (ANN) circuit blocks by using subthreshold floating-gate MOS (FGMOS) transistors and a neuron circuit is implemented. The circuit blocks, four-quadrant analog current multiplier and FGMOS based differential pair, have been designed and simulated in CADENCE environment with TSMC 0.35μm process parameters. Using the proposed...
A novel method to diagnose the bearing fault is presented. The proposed method is based on the analysis of the bearing vibration signals using Singular Spectrum Analysis (SSA). SSA is a non-parametric technique of time series analysis that decomposes the acquired bearing vibration signals into an additive set of time series to extract information correlated with the condition of the bearing. Information...
Here we have presented an alternate ANN structure called functional link ANN (FLANN) for channel equalization. In contrast to a feed forward ANN structure i.e. a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which non-linearity is introduced by enhancing the input pattern with nonlinear function expansion. A novel method of training the FLANNs using PSO Algorithm...
In this paper, the sliding-mode lag synchronization control scheme is proposed based on the neural network to synchronize two different delayed chaotic systems. An integral delayed sliding surface is presented to design the sliding mode control. The lag synchronization controller is achieved by combining the RBF (radial basis function) neural network with sliding-mode control. Numerical simulations...
Performance is an important non functional aspect to be considered for any software system. Software Performance Engineering (SPE) is an approach to predict the performance of a software system early in the life cycle. In this paper we present a neural network model for the performance prediction of Multi-Agent system at the early stages of development. We used Feed forward back propagation neural...
In this paper we propose a robust channel estimator for Long Term Evolution (LTE) downlink highly selective using neural network. This method uses the information provided by the reference signals to estimate the total frequency response of the channel in two phases. In the first phase, the proposed method learns to adapt to the channel variations, and in the second phase it predicts the channel parameters...
The paper presents a neural network based predictive control (NPC) strategy to control nonlinear chemical process or system. Multilayer perceptron neural network (MLP) is chosen to represent a Nonlinear autoregressive with exogenous signal (NARX) model of a nonlinear process. Based on the identified neural model, a generalized predictive control (GPC) algorithm is implemented to control the composition...
Neural networks are often selected as tool for software effort prediction because of their capability to approximate any continuous function with arbitrary accuracy. A major drawback of neural networks is the complex mapping between inputs and output, which is not easily understood by a user. This paper describes a rule extraction technique that derives a set of comprehensible IF-THEN rules from a...
This paper presents the theoretical analysis, design and simulation of a single phase single stage boost dc-ac converter powered from PV array. The main attribute of the boost inverter topology is the fact that it generates an ac output voltage larger than the dc input one, depending on the instantaneous duty cycle. This paper proposes an accurate solar panel simulation to incorporate the temperature...
In this paper, credibility evaluation issue of missile flight simulation model is studying by applying neural network technique. Aiming at the subsistent insufficiency of model validation method in application, we present a credibility evaluation method based on neural network. Which uses the powerful ability of nonlinearity mapping of neural network by utilizing missile flight state data of simulation...
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