This paper investigates distributed formation control of multi-mobile robot systems with collision avoidance. A novel nested constraints based anti-disturbance formation control scheme is established, which contains t...
详细信息
This paper investigates distributed formation control of multi-mobile robot systems with collision avoidance. A novel nested constraints based anti-disturbance formation control scheme is established, which contains two parts. In the first part, a formation signal generator is constructed on the communication network by using proper distributed cooperative control approaches and artificial potential field-based methods, such that it "completes" the desired formation control task in its outputs. In the second part, by combining proper disturbance estimations, some nonlinear tracking controllers are designed for the robots to track the corresponding outputs of the generator asymptotically. A "nested constraint mechanism" is put forward accordingly and applied to limit the generator’s outputs and the robots’ tracking errors. In this way, the studied multi-mobile robot systems realize the formation control goal with collision avoidance. Compared with existing results, the proposed method has a better plug-and-play feature to deal with the tight encapsulations of the practical robot products, and has better convergence performances with the existence of disturbances. Some experiments are given to validate the effects of the proposed methods.
This paper studies the distributed estimation problem of sensor networks where the noise parameters are unknown and some sensors cannot obtain the measurements. The expectation maximization (EM) algorithm integrating ...
详细信息
ISBN:
(纸本)9781665476881
This paper studies the distributed estimation problem of sensor networks where the noise parameters are unknown and some sensors cannot obtain the measurements. The expectation maximization (EM) algorithm integrating Kalman filtering algorithm, which is called the EM-KF algorithm, is adopted to sensor networks. Simulation examples are given to illustrate the effectiveness of the algorithm. By using LSTM network, and LSTM-KF algorithm is further proposed to improve the accuracy of EM-KF algorithm.
With the increasing awareness of environmental protection, the solar photovoltaic (PV) industry has been developing dramatically in recent years. PV module is an important part of PV power generation system. In all th...
详细信息
ISBN:
(纸本)9781665478977
With the increasing awareness of environmental protection, the solar photovoltaic (PV) industry has been developing dramatically in recent years. PV module is an important part of PV power generation system. In all the defect types of PV modules, hotspots occur more frequently and cause more serious damage. Therefore, it is necessary to detect hotspots. An approach is proposed using saliency analysis method for hotspot detection, combing the cognitive property about visual saliency and the temperature property of hotspots. Not only does this approach not require manual threshold setting, but also it does not require a large number of learning samples. This approach can also achieve the defect diagnosis and hotspot location when compared with the electrical characterization method. The infrared thermal (IRT) images trained in experiments are obtained using the thermographic camera FLIR Vue Pro with the unmanned aerial vehicle from a PV plant in Jiangsu, China. Altogether 135 IRT images are collected and 1020 PV modules are extracted from these images. Experiments have proved great accuracy and robustness when using the proposed method to detect hotspots.
This paper focuses on the development of a control scheme capable of tracking contact forces explicitly. Specifically, the nonlinear observer, admittance control and adaptive sliding mode control are integrated into a...
详细信息
ISBN:
(纸本)9781665478977
This paper focuses on the development of a control scheme capable of tracking contact forces explicitly. Specifically, the nonlinear observer, admittance control and adaptive sliding mode control are integrated into a single framework. When the force sensor is absent, a nonlinear observer, which serves as a reaction force observer, can be used to estimate the contact force. Furthermore, in order to track the force profile explicitly, admittance control is introduced to transform the desired contact force into the desired position signal. An adaptive sliding mode controller is designed to track the desired position and meanwhile compensate the estimation errors of contact forces caused by nonlinear observer. The stability of the whole system under the proposed controller can be guaranteed by the Lyapunov function. Finally, several simulations are reported to demonstrate the effectiveness of the proposed approach.
Accurate ultra-short-term photovoltaic (PV) power forecasting is crucial for the real-time scheduling of grid systems. However, the inherent variability of solar energy makes this task extremely challenging. To enhanc...
详细信息
ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
Accurate ultra-short-term photovoltaic (PV) power forecasting is crucial for the real-time scheduling of grid systems. However, the inherent variability of solar energy makes this task extremely challenging. To enhance PV power forecasting, this paper introduces a novel hybrid model named PVTimesNet, designed to harness the strengths of Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) for effective feature extraction. PVTimesNet consists of two parallel branches: the CNN1d branch, which captures correlations between multiple variables and adjacent time steps, and the LSTM branch, which learns the temporal dependencies within the PV power sequences. The features extracted by both branches are then concatenated and passed through a fully connected layer to generate multi-step PV power forecasts. Experimental results demonstrate that for forecast horizons of 1 to 4 hours, the proposed model significantly outperforms individual models and other CNN-LSTM hybrid structures. Additionally, it exhibits superior performance compared to related methods for longer forecast horizons.
A flexible active safety motion (FASM) control approach is proposed for the avoidance of dynamic obstacles and the reference tracking in robot manipulators. The distinctive feature of the proposed method lies in its u...
详细信息
With the vigorous development of the photovoltaic industry, how to improve the efficiency of photovoltaic power generation has become an important issue, among which partial shadow occlusion is an important reason aff...
详细信息
Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image alignment due to the lack of explicit 2D...
详细信息
Image retrieval has been employed as a robust complementary technique to address the challenge of Unmanned Aerial Vehicles (UAVs) self-positioning. However, most existing methods primarily focus on localizing objects ...
详细信息
In recent years, hashing methods have been popular in the large-scale media search for low storage and strong representation capabilities. To describe objects with similar overall appearance but subtle differences, mo...
详细信息
暂无评论