In the practical application,Brushless DC motor(BLDCM) faces various disturbances including parametric uncertainties,load disturbance and unmodeled *** disturbances can be divided into two types of periodic disturbanc...
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ISBN:
(纸本)9781467397155
In the practical application,Brushless DC motor(BLDCM) faces various disturbances including parametric uncertainties,load disturbance and unmodeled *** disturbances can be divided into two types of periodic disturbances(sinusoidal/cosinoidal) and aperiodic(slowly-varying or constant) *** ripples can be seen as the result of a plurality of periodic interference signals of different frequencies acting on the *** the paper we propose a composite control scheme combining integral sliding mode control(ISMC) based on disturbance observer(DO) embedded with the internal model principle to improve the speed performance of *** disturbance observer,such as extended state observer(ESO) can only asymptotically estimate slowly-varying or constant disturbances and is not good at estimating periodic *** we combine internal model of disturbance into disturbance observe for high ***,the estimates are introduced in the feedforward compensation,and a composite speed controller is *** last,experimental comparisons with conventional proportional-integral(PI) and ISMC+ESO,are given to validate the effectiveness of the proposed method.
The localization problem for sensor networks with communication and measurement noises is studied in this paper. A robust distributed iterative algorithm called ECHO-CMN is presented based on the signed barycentric co...
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ISBN:
(纸本)9781509015740;9781509015733
The localization problem for sensor networks with communication and measurement noises is studied in this paper. A robust distributed iterative algorithm called ECHO-CMN is presented based on the signed barycentric coordinate representation, which can be calculated only by relative distance measurements. In the algorithm, a dither is added to the sensor states before quantization to randomize the quantization error. To attenuate the communication noise, a gain parameter which decays to zero is used. An unbiased distance estimator is constructed, and nodes can take advantage of the estimator to update the distance estimation before each localization iteration. It can be proved that ECHO-CMN converges to the exact location of each sensor almost surely under some mild assumptions on the noise. Numerical studies illustrate the proposed localization algorithm.
This paper studies the similar formation algorithm of multi-agent systems with biased measurement errors. When relative position measurements contain biased errors, the existing similar formation algorithm is not mean...
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ISBN:
(纸本)9781509015740;9781509015733
This paper studies the similar formation algorithm of multi-agent systems with biased measurement errors. When relative position measurements contain biased errors, the existing similar formation algorithm is not mean reachable in general. This paper proposes a modified similar formation algorithm with which agents can overcome biased measurement errors online and reach any desired generic formation shape in the expectation sense. The formation error is globally uniformly bounded in the mean square sense.
In the copper electrolytic refining process, the short-circuit failure among the electrodes usually exists. When it occurs, the temperature distribution is often abnormal, accompanied by local or overall overheating. ...
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In the copper electrolytic refining process, the short-circuit failure among the electrodes usually exists. When it occurs, the temperature distribution is often abnormal, accompanied by local or overall overheating. This paper proposes a novel processing method for infrared temperature images to effectively detect the short-circuit fault and locate the accurate malfunctioning spots. The design procedure contains contrast enhancement, filter denoising, edge detection, image segmentation, high temperature electrode positioning. Finally, experimental results show that the proposed method can guarantee real-time processing of the infrared image of the electrolytic cell and accurately mark the malfunctioning position of electrodes with high temperature fault.
This paper deals with cooperative estimation and control for second-order agents formation tracking a set of given orbit in an external flowfield,where only direction of flow inertial velocity is spatiotemporal and kn...
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ISBN:
(纸本)9781509009107
This paper deals with cooperative estimation and control for second-order agents formation tracking a set of given orbit in an external flowfield,where only direction of flow inertial velocity is spatiotemporal and known.A novel coordinated adaptive estimator based on local neighbor-to-neighbor information is proposed to estimate the flow *** is shown that our previous geometric extension design,consensus and adaptive backstepping method can be combined together to construct the robust formation tracking controller under bidirectional *** theoretical result is proved by the numerical simulation.
This paper mainly studies the angle tracking problem in electronic throttle system with unknown time-varying disturbances. Firstly, generalized proportional integral observer (GPIO) is used to estimate the time-varyin...
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This paper mainly studies the angle tracking problem in electronic throttle system with unknown time-varying disturbances. Firstly, generalized proportional integral observer (GPIO) is used to estimate the time-varying disturbances including model uncertainties, friction torque and spring initial torque. Secondly, a composite controller combining disturbance estimation and backstepping control method is designed, which is called the BSC+GPIO method. This control method is convenient to implement and the disturbance rejection capability is enhanced by feedforward compensating the estimated value of system disturbances. The simulation results show the effectiveness of the proposed method.
In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in th...
In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in the image poses a huge challenge for smoke detection and other video analysis tasks. Appropriate depth level estimation provide significant prior knowledge for subsequent identification and detection. For landscape images, we can approximate the air transmittance to depth information for histogram analysis. The depth value is segmented by a multi-threshold segmentation algorithm, and the resulting image can be used for forest fireworks detection and the like. This method does not rely on samples and classifiers, and the algorithm does not require training. The final experimental results show that the depth level estimation of a single landscape image based on the dark channel prior can achieve good results.
Face detection and location technique is a hot research direction during recent years. Especially, driver face detection on highway is still a challenging problem in social safty deserving research. This paper propose...
Face detection and location technique is a hot research direction during recent years. Especially, driver face detection on highway is still a challenging problem in social safty deserving research. This paper proposes a novel algorithm based on the improved Multi-task Cascaded Convolutional Networks (MTCNN) and Support Vector Machine (SVM) to realize accurate face region detection and feature location of driver's face on highway, predicting face and feature location via a coarse-to-fine pattern. The proposed algorithm is verified under various complex highway conditions. Experimental results show that the proposed model shows satisfied performance compared to other state-of-the-art techniques used in driver face detection and alignment, keeping robust to the occlusions, varying pose and extreme illumination on highway.
Background extraction is an important step in vehicle detection. In the actual scene, change of illumination will lead to a tremendous background change. It is necessary to update the background model
ISBN:
(纸本)9781467389808
Background extraction is an important step in vehicle detection. In the actual scene, change of illumination will lead to a tremendous background change. It is necessary to update the background model
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