Cyber-physical System (CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing (CS) theory...
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Cyber-physical System (CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing (CS) theory is applied to the sampling compression process of CPS system. The CS theory was used to the sampling compression method of CPS system. The Bernoulli circulant matrix, which is easy to be realized and stored, and its construction algorithm were designed to simplify the realization of CS theory in CPS. It is concluded that for random data set, the compression ratio increases from 14.06% to 42.18% and the reconstruction error decreases from 27.65 to 1.28 with increasing repetition times. Note that the sampling time are around tens of microseconds and the reconstruction time are around several milliseconds, which indicates a high real-time performance for CPS. In addition, for image data set, the compression ratios are about 42.90% which indicates a high compression ratio and huge storage resources saving. More importantly, the sampling time and reconstruction time are only several microseconds and several seconds respectively, which indicates a high real-time performance for CPS.
— A new modified repetitive control strategy based on the Takagi-Sugeno fuzzy model is presented for an affine nonlinear system to track a periodic reference and reject a periodic disturbance. Then, a parallel distri...
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Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC ci...
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Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC circuit, the maximum power point tracking algorithm based on parabolic approximation method is used. On the basis of analyzing the principle of various tracking methods, the key technology of parabola approximation can be found to find the exact maximum power point.
This paper investigates the stability of neural networks with a time-varying delay. Based on the good effectiveness of the augmented Lyapunov-Krasovskii functional (LKF), some useful integral vectors are summarized an...
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This paper investigates the stability of neural networks with a time-varying delay. Based on the good effectiveness of the augmented Lyapunov-Krasovskii functional (LKF), some useful integral vectors are summarized and used to construct single integral terms with augmented quadratic integrand so as to develop a novel augmented LKF candidate. Then an extended reciprocally convex matrix inequality and an auxiliary function-based inequality are utilized to estimate the derivative of the LKF. As a result, an improved stability criterion is established. Finally, the advantage of proposed method is demonstrated by a numerical example.
To overcome the shortcomings of high cost, maintenance difficulties in traditional vehicle detect ion methods. This paper presents a novel vehicle detection method used in the military field. The anisotropic magneto r...
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To overcome the shortcomings of high cost, maintenance difficulties in traditional vehicle detect ion methods. This paper presents a novel vehicle detection method used in the military field. The anisotropic magneto resistive (AMR) sensor is used to detect geomagnetic disturbances in real time, meanwhile, the ultrasonic distance-measuring sensor is adopted to determine the position of the target vehicle and avoid miscalculation. To reduce detection delay, a scheme containing dual AMR sensors and wireless communication module for information transferring is used on this detection system. In order to verify the effectiveness of the detection system, a mathematical model of vehicle detection based on geomagnetic disturbance detection is established. According to the test results, the influence cased by different content of ferromagnetic material and detection distance is analyzed. Finally, the related experiments on the effects of different ferromagnetic contents on the geomagnetic disturbance at different detection distances are carried out. The experimental results verify the correctness of the mathematical model proposed in this paper, and further verify the effectiveness of the detection system. This detection system possesses many prominent advantages such as low-cost, long-life, good performance of real time, convenience.
T0616. The temperature accuracy of the steel coil is directly affected the production quality of the steel plate. In the annealing furnace temperature control system, strip temperature control is mainly decided by var...
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Aiming at the problems of slow recognition, low efficiency and degree of automation in handwritten letter recognition system at present, a handwritten letter recognition system based on extreme learning machine is des...
Aiming at the problems of slow recognition, low efficiency and degree of automation in handwritten letter recognition system at present, a handwritten letter recognition system based on extreme learning machine is designed in this paper. The system is implemented by mixed programming with MATLAB and visual studio, it can reads, normalize, binarize and extract the handwritten letter images. The real-time interactive recognition of handwritten letters can be realized on the basis of training the simple pictures by using the identification model of the extreme learning machine algorithm. The experimental results show that the handwriting recognition system based on extreme learning machine designed in this paper can recognize 98.82% of handwritten letters and greatly reduce learning and testing time. Compared with BP neural network and other recognition algorithms, its training times have been reduced by hundreds or even thousands of times. At the same time, there is no manual intervention in the entire learning and testing process, which improves the automation of handwriting recognition.
The weighted complementarity problem is an extension of the standard finite dimensional complementarity problem. It is well known that the smoothing-type algorithm is a powerful tool of solving the standard complement...
The weighted complementarity problem is an extension of the standard finite dimensional complementarity problem. It is well known that the smoothing-type algorithm is a powerful tool of solving the standard complementarity problem. In this paper, we propose a smoothing-type algorithm for solving the weighted complementarity problem with a monotone function, which needs only to solve one linear system of equations and performs one line search at each iteration. We show that the proposed method is globally convergent under the assumption that the problem is solvable. The preliminary numerical results indicate that the proposed method is effective and robust for solving the monotone weighted complementarity problem.
An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our met...
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An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our method is the use of white-balancing to normalize the scene illumination and link function to transform the reflectance, we use a radial basis function network to model the mapping between camera-specific RGB values and specific reflectance spectra. Experimental results indicate that the proposed method significantly outperforms currently existing methods in terms of spectral error and shape especially under the illumination not present in the training process.
A plant is controlled remotely on a network for a networked control system. Disturbances from the network and surroundings may deteriorate the control performance of such a system. To solve this problem, this paper pr...
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A plant is controlled remotely on a network for a networked control system. Disturbances from the network and surroundings may deteriorate the control performance of such a system. To solve this problem, this paper presents a new method of suppressing an exogenous disturbance for those control systems. The control system has a state observer to estimate the state of the plant and an equivalent-input-disturbance (EID) estimator to produce an estimate of the disturbance on the control input channel in a real-time fashion. The system is divided into two subsystems for the analysis of system stability. A stability condition of the control system with a time-varying delay is presented in terms of a linear matrix inequality. Simulations demonstrate the validity of the method. And a comparative study shows the superior of our method to a conventional Smith-EID control method.
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