In order to compensate for the impact of time delay on the estimation of object feature point image and image Jacobian matrix and improve the control precision of image-based visual servo system, a Kalman filtering al...
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In order to compensate for the impact of time delay on the estimation of object feature point image and image Jacobian matrix and improve the control precision of image-based visual servo system, a Kalman filtering algorithm with colored noise is proposed to obtained the current motion state estimation of the feature point with time-delay compensation in the image space, then the accurate image Jacobian matrix under time delay can be obtained. For the above, the following work will be done in this paper: (1) the current motion state estimation of the feature point in the image space is predicted by Kalman filtering algorithm, combined with practical applications, measurement noise is usually as colored noise and can be regarded as a one-order Markov sequence excited by Gauss white noise, then a Kalman filtering recursive model can be derived according to the variance minimization principle of the estimation error;(2) to obtain the measurement vectors estimation which cannot be acquired in the Kalman filtering model owing to the existence of time delay, the relationship between the motion state of the feature point at the prior and later point is established, and a polynomial is fitted by using some of the observed data under the relationship to realize the measurement vectors estimation in the time-delay period. Thus the estimation of the motion state of the feature point at the current time in the image space can be obtained, and the estimation of image Jacobian matrix with time-delay compensation can be obtained. Experimental results validate the feasibility and superiority of this method.
This paper investigates the problem of observer-based output feedback control for networked controlsystems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary wit...
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This paper investigates the problem of observer-based output feedback control for networked controlsystems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.
With the universal application of camera in intelligent vehicles, visual place recognition has become a major problem in intelligent vehicle localization. The traditional solution is to make visual description of plac...
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ISBN:
(纸本)9781538644539
With the universal application of camera in intelligent vehicles, visual place recognition has become a major problem in intelligent vehicle localization. The traditional solution is to make visual description of place images using hand-crafted feature for matching places, but this description method is not very good for extreme variability, especially for seasonal transformation. In this paper, we propose a new method based on convolutional neural network (CNN), by putting images into the pre-trained network model to get automatically learned image descriptors, and through some operations of pooling, fusion and binarization to optimize them, then the similarity result of place recognition is presented with the Hamming distance of the place sequence. In the experimental part, we compare our method with some state-of-the-art algorithms, FABMAP, ABLE-M and SeqSLAM, to illustrate its advantages. The experimental results show that our method based on CNN achieves better performance than other methods on the representative public datasets.
In networked load frequency control (LFC) systems, time-varying delays could come from two aspects: measurements' transmission from power plant to control center and control signals from the control center to plan...
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In networked load frequency control (LFC) systems, time-varying delays could come from two aspects: measurements' transmission from power plant to control center and control signals from the control center to plant side, because of the use of open communication networks. Those delays can affect the dynamic performance and the stability of the system. In this paper, the two delays are considered in one-area LFC system, instead of combining these two delays into one, when the delay-dependent stability analysis is carried out by using Lyaponuvtheory and linear matrix inequality (LMI) technique. Moreover, the dynamic delay interval method is employed to derive less conservative delay-dependent stability criteria for such time-delay system compared with the existing results. Finally, the effectiveness of the proposed criteria are verified by two case studies.
This paper investigates decentralized tracking control(DTC) problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual st...
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ISBN:
(纸本)9781538629185
This paper investigates decentralized tracking control(DTC) problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual states of coupled subsystems in interconnection terms with their desired states,the norm-boundedness assumption can be *** on local neural network(NN) observers,unknown subsystems can be *** helps to obtain the local desired control with corresponding desired *** establishing a proper local cost function,the local tracking error control is derived via local critic NN and the identified input gain *** the entire error caused by replacement,identification and critic NN approximation,an adaptive robust term is added to construct the robust local cost function that reflects the entire error,regulation and control ***,the asymptotic stability can be guaranteed for the closed-loop tracking system via Lyapunov stability *** demonstrate the effectiveness of the proposed DTC,simulation on a hard spring connected parallel inverted pendulum system is given.
This paper investigates the passivity-based fault detection of semi-Markov jump systems with time-varying delays. By constructing the filter type residual generator and model transformation, the augmented error system...
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This paper investigates the passivity-based fault detection of semi-Markov jump systems with time-varying delays. By constructing the filter type residual generator and model transformation, the augmented error system is first established. Then, by means of Lyapunov-Krasovskii approach, fault detection conditions are given such that the augmented error systems can satisfy the passivity performance. The desired fault detection gains can be obtained with the help of matrix techniques. The simulation example is presented to show the validity of the design method.
Urban Traffic control (UTC) plays an essential role in intelligent Transportation System (ITS) but remains difficult. Since model-based UTC methods may not accurately describe the complex nature of traffic dynamics in...
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The hyper-spectral image contains spectral and spatial information,which increases the ability and precision of objects *** the classification value of hyper-spectral imaging technology within various applications,use...
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The hyper-spectral image contains spectral and spatial information,which increases the ability and precision of objects *** the classification value of hyper-spectral imaging technology within various applications,users often find it difficult to effectively apply in practice because of the effect of light,temperature and wind in outdoor *** research presented a new classification model for outdoor farmland objects based on near-infrared(NIR)hyper-spectral *** involves two steps including region of interest(ROI)acquisition and establishment of classifiers.A distance-based method for quantitative analysis was proposed to optimize the reference pixels in ROI acquisition *** maximum likelihood(ML)and support vector machine(SVM)were used for farmland objects *** performance of the proposed method showed that the total classification accuracy based on the reference pixels was over 97.5%,of which the SVM-M model could reach 99.5%.The research provided an effective method for outdoor farmland image classification.
In this paper, the influences of system parameters on stochastic resonance output effect is analyzed, which takes the multi-stable stochastic resonance system as the model. That is, the vibration condition of multi-st...
In this paper, the influences of system parameters on stochastic resonance output effect is analyzed, which takes the multi-stable stochastic resonance system as the model. That is, the vibration condition of multi-stable stochastic resonance system, and weak signal detection method based on the multi-stable stochastic resonance under α stable noise is investigated. Then considering the real-time detection of weak signals in practical engineering, the multi-stable stochastic resonance system parameters a, b, c are optimized by particle swarm optimization(PSO), which takes the output signal-to-noise ratio(SNR out ) as the fitness function. Finally, multi-frequency weak signals detection with α stable noise is achieved, and the above method is applied to the vibration fault diagnosis of turbine. Both simulation and experiment results show that this method can quickly and effectively detect multi-frequency weak signals submerged in strong noise background, which lays a foundation for its application in engineering practice.
1 Introduction With the development of science and technology,it becomes difficult to deal with modern complex equipment with the traditional methods of fault *** a new kind of multi-layer neural network learning algo...
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1 Introduction With the development of science and technology,it becomes difficult to deal with modern complex equipment with the traditional methods of fault *** a new kind of multi-layer neural network learning algorithm,deep learning has been paid more and more attention due to its remarkable advantages in dealing with
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