In this paper, the tracking control of a class general non-affine discrete-time unknown systems represented by the nonlinear autoregressive moving average with eXogenous input (NARMAX) representation is discussed. An ...
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ISBN:
(数字)9781424487387
ISBN:
(纸本)9781424487370
In this paper, the tracking control of a class general non-affine discrete-time unknown systems represented by the nonlinear autoregressive moving average with eXogenous input (NARMAX) representation is discussed. An equivalent affine-like representation in terms of the tracking error dynamics is first obtained from the original nonaffine nonlinear discrete-time system so that a robust adaptive critic-based neural network controller can be developed. The control scheme consists of an action NN for compensating the unknown system dynamics, and a critic NN to approximate certain strategic utility function and to tune the action NN weights. The NN weights are tuned an online manner without the need of the knowledge of the system dynamics. By using the standard Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error is shown. Simulation results are given substantiate the theoretical conclusions.
In water treatment engineering, pH value is one of the most important parameters for optimizing experimental results. Because pH process has serious nonlinearity and delay, it is difficult to obtain effective control ...
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In water treatment engineering, pH value is one of the most important parameters for optimizing experimental results. Because pH process has serious nonlinearity and delay, it is difficult to obtain effective control for conventional PID controllers without a precise mathematical model. According to the behavior of pH in the process of water treatment, a fuzzy control approach is proposed. The fuzzy controller is simulated with the actual data, and the simulation results demonstrate that the approach is efficient and feasible. In present paper, we construct a novel water treatment system based on microwave plasma technique and TiO2 photocatalytic technique. Experimental results show that the system can enable the value of chemical oxygen demand (COD) and heavy metal ions in water up to the Standards for Drinking Water Quality (GB5749-2006), also it can effectively reduce costs when the fuzzy controller is employed.
Abstract Pattern recognition techniques have been widely applied for fault diagnosis. In this paper, two different forms, named serial form and simultaneous form, of pattern recognition based fault detection and ident...
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Abstract Pattern recognition techniques have been widely applied for fault diagnosis. In this paper, two different forms, named serial form and simultaneous form, of pattern recognition based fault detection and identification systems are discussed. The optimal form is selected by a performance assessment rule which is based on the overall fault diagnosis system loss. Beside of considering the fault detection and isolation performance of the classifiers, the misclassification costs in both of the fault detection and isolation stages have also been considered for selecting the optimal form. In order to compare the performance of these two forms, two novel fault detection and isolation approaches integrating kernel principal component analysis (KPCA) and support vector data description (SVDD) are proposed subsequently. A simulation case study of Tennessee Eastman (TE) process is presented to evaluate the proposed fault detection and isolation methods.
For dynamic batch process monitoring, a two-dimensional dynamic modeling framework has recently been formulated, which is based on a two-dimensional autoregressive model and the principal component analysis (PCA) meth...
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Fluorescence has been proved to be a versatile and useful tool for animal in vivo imaging. It has been used widely in biomedical research and drug discoveries. With the recent development of the technology and instrum...
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As a large-capacity public transport tool, the railway system needs high stability and reliability. In order to reduce cost and satisfy the safety requirements of train control system, a novel safety-related digital i...
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As a large-capacity public transport tool, the railway system needs high stability and reliability. In order to reduce cost and satisfy the safety requirements of train control system, a novel safety-related digital input system is designed and implemented based on architectural constraints of safety-related systems and the analysis of the working principle of the specific digital input system. This system is designed as 2-out-of-3 architecture on the basis of vital computer. The method of fault diagnosis has been improved after the analysis of the practical situation. That is, the detection signal sent by the external pulse transmitter module contains the circuit fault information after the signal pass through the input circuit, and the real-time self-diagnosis will be done after using the supporting software to deal with timing diagram. The system uses less CPU resources to achieve the high diagnostic efficiency, which improves safety failure rate. And its failure analysis is discussed. The Markov Model is used to verify the Safety Integrity Level (SIL) of the safety-related system. The analysis shows that this design, with easy implementation and low cost, meets the requirements of SIL4 in railway and is more reliable.
In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intel...
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In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intelligent traffic. A block-based Gaussian mixture background modeling method for object detection is presented to reduce the computational complexity of moving vehicle object abstraction. An adaptive tracking algorithm fused with color features and texture features is described to better adapt the traffic scene variation. The experimental results show that the proposed algorithm can effectively deal with the complex urban traffic conditions and the tracking performance is better than the conventional particle filter method and single feature based non-adaptive object tracking method.
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