Achieving asymptotical cooperative goal for multi-agent systems(MASs)with non-autonomous leaders(i.e.,leaders with nonzero inputs)is a critical but challenging *** approach is to use discontinuous controllers which ma...
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Achieving asymptotical cooperative goal for multi-agent systems(MASs)with non-autonomous leaders(i.e.,leaders with nonzero inputs)is a critical but challenging *** approach is to use discontinuous controllers which may cause chattering phenomenon in practical *** to achieve the asymptotical goal via a chattering free cooperative controller remains to be open so *** this paper,an adaptive continuous controller is designed to achieve zero error consensus tracking in multiple Lur’e systems with a non-autonomous leader under directed switching ***,an unknown input observer(UIO)based on relative outputs is given to estimate the relative full *** an adaptive continuous controller is designed by introducing a decay function which remains positive into the term that plays the role of eliminating the impacts of leader’s nonzero ***,by using multiple Lyapunov functions(MLFs)technique,it is proven that zero error consensus tracking can be achieved if the average dwell time(ADT)is greater than a positive ***,theoretical result is verified by performing simulations on Chua’s *** with existing work,the proposed controller can not only achieve asymptotical consensus,but also is chattering free.
Particulate environment is frequently encountered in the millimeter wave propagation path. The particles usually produce scattering and absorption to the millimeter wave. Unfortunately, these particles usually have di...
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ISBN:
(数字)9781728129938
ISBN:
(纸本)9781728129945
Particulate environment is frequently encountered in the millimeter wave propagation path. The particles usually produce scattering and absorption to the millimeter wave. Unfortunately, these particles usually have different size, ingredients and even a mixture of many elements. This paper presents a preliminary study of the attenuation of particles on millimeter wave transmission. The dielectric property of water sand and ice were also discussed. The study was conducted at 110 GHz and 220 GHz. Calculation was based on the Mie theory. A full wave simulation was also conducted to better understand the attenuation effect.
Currently, the prevailing approach in pedestrian detection involves leveraging deep learning techniques. However, effectively detecting pedestrian objects at small scales continues to pose a significant challenge in t...
Currently, the prevailing approach in pedestrian detection involves leveraging deep learning techniques. However, effectively detecting pedestrian objects at small scales continues to pose a significant challenge in this field of research. Moreover, many algorithms prioritize accuracy improvement, making it difficult to deploy them in real-world scenarios. This paper proposes an edge device-friendly object detection method. We introduce a target extraction module with a minimal number of non-linear units to preserve fine-grained information in the network. Additionally, we design a trapezoidal FPN structure based on the structural re-parameterization technique, and optimize it specifically for edge devices. Furthermore, we construct a hardware platform to validate the feasibility of our algorithm in real-world applications. In the experimental section, we demonstrate that our proposed method outperforms comparative algorithms on the Caltech pedestrian dataset, while maintaining high speed on edge devices.
In order to improve the endurance of unmanned aerial vehicles (UAVs), a power supply controller with automatic switching between solar energy and battery was designed. The controller is mainly composed of an AT89C51 s...
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In order to solve the bounding box deviation while the object moves rapidly, which will cause the loss of the object, an improved Kernelized Correlation Filter object tracking algorithm is proposed based on motion est...
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In order to solve the bounding box deviation while the object moves rapidly, which will cause the loss of the object, an improved Kernelized Correlation Filter object tracking algorithm is proposed based on motion estimation. The block-matching algorithm is used to estimate the motion of the tracking object in the adjacent frames of the video sequence, and the estimated results are quantified to judge the severity of the object’s motion. Then the size of the search box is adaptively adjusted. Two data sets of both OTB100 and OTB50 are selected for the experiments. The experimental results show that the improved algorithm can effectively solve the problem of object loss caused by rapid object movement and achieve long-term stable tracking of objects.
In order to improve the utilization efficiency of solar energy, based on the in-depth study of the characteristics of solar energy, a control scheme based on daily motion trajectory was designed. In this scheme, singl...
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ISBN:
(纸本)9781728190181;9781728190198
In order to improve the utilization efficiency of solar energy, based on the in-depth study of the characteristics of solar energy, a control scheme based on daily motion trajectory was designed. In this scheme, single chip microcomputer is used as the controller to realize the output of SPWM waveform, and the compound PID with multiplexing selection is used to control the Angle of solar panel, so as to achieve the effect of fast and sensitive tracking of solar illumination. Through the angle sensor, on-line monitoring of the angle data of the solar panel, according to the intelligentcontrol optimization algorithm, combined with single-chip microcomputer control technology, a more optimized control scheme is proposed. The experimental data show that the design effect is good and the expected control goal is achieved.
In order to accurately evaluate the working state of RV reducer, a fault identification method based on the fault identification model established by Self-Organizing Feature Map (SOM) Neural Network is proposed. First...
In order to accurately evaluate the working state of RV reducer, a fault identification method based on the fault identification model established by Self-Organizing Feature Map (SOM) Neural Network is proposed. Firstly, the data measured by the RV reducer test platform are analyzed by wavelet to obtain the wavelet coefficient. Then, combined with the efficiency data of RV reducer, the mean square frequency, center of gravity frequency and frequency variance of the two groups of data are calculated after Fourier transform and power spectrum analysis. After optimization, several eigenvalues are obtained. The eigenvalues are input into the competitive neural network and SOM neural network to establish the fault identification model. Finally, the results of the fault identification model established by the competitive neural network and SOM neural network are compared. The prediction results show that the fault identification model established by SOM neural network can effectively determine the working state of RV reducer.
It is difficult for a robot to capture object which is thrown out in the environment with natural wind. Equation of state and measurement of the object in the environment with natural wind is studied. Using the measur...
It is difficult for a robot to capture object which is thrown out in the environment with natural wind. Equation of state and measurement of the object in the environment with natural wind is studied. Using the measurement equation and the state equation when there is no natural wind, the average acceleration of the object caused by natural wind can be estimated. Moreover, the variance of the object acceleration caused by natural wind can be estimated using the statistical characteristics and probability distribution of natural wind. Then a method for robot capturing the object based on Kalman filter is proposed. Simulation results show that the trajectory of the object changes obviously when two groups of typical natural wind are used. The object trajectory can be tracked by the robot accurately after it deviates from the object trajectory for about eight sampling periods.
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