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Dynamics analysis and numerical implementations of a diffusive predator–prey model with herd behaviour and Allee effect 具有群体行为和Allee效应的扩散捕食-猎物模型的动力学分析与数值实现
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-06-23 DOI: 10.1080/21642583.2022.2079572
Wenbin Yang, Danqing Li
This paper is concerned with a prey–predator system involving herd behaviour and strong Allee effect. First, the local stability analysis of all the possible equilibrium points are investigated. Second, the existence of Hopf bifurcation around the unique positive equilibrium are carried out. Finally, this paper is ended with a numerical simulation to understand the dynamics of the system. As it turns out that the ‘Allee effect constant’ plays a very important role in biological invasion mechanism, such as controlling and preventing biological invasion or invading successfully.
本文研究了一个具有群体行为和强Allee效应的捕食系统。首先,研究了所有可能平衡点的局部稳定性分析。其次,证明了唯一正平衡点周围Hopf分岔的存在性。最后,通过数值模拟来了解系统的动力学特性。结果表明,“Allee效应常数”在生物入侵机制中起着控制和防止生物入侵或成功入侵的重要作用。
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引用次数: 1
Target detection based on a new triple activation function 基于新的三重激活函数的目标检测
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-06-23 DOI: 10.1080/21642583.2022.2091060
Guanyu Chen, Q. Wang, Xiang Li, Yanyun Zhang
As one of the important parts of Neural Network, activation function plays a very important role in model training in Neural Network. In this paper, the status quo, advantages and disadvantages of the existing common activation functions are analysed, and a new activation function is proposed and applied to target detection. To test the performance of the new activation function, this paper compares it with the ReLU activation functions on a variety of Neural Networks and data sets, and not only analyses the performance of the activation function itself but also verifies the effectiveness of the activation function in target detection.
激活函数作为神经网络的重要组成部分,在神经网络的模型训练中起着非常重要的作用。本文分析了现有常用激活函数的现状、优缺点,提出了一种新的激活函数,并将其应用于目标检测。为了测试新激活函数的性能,本文将其与ReLU激活函数在各种神经网络和数据集上进行了比较,不仅分析了激活函数本身的性能,还验证了激活函数在目标检测中的有效性。
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引用次数: 1
An underwater target recognition method based on improved YOLOv4 in complex marine environment 基于改进YOLOv4的复杂海洋环境下水下目标识别方法
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-06-06 DOI: 10.1080/21642583.2022.2082579
Jili Zhou, Q. Yang, Huijuan Meng, D. Gao
In the marine environment, there are problems such as complex background and low illumination, resulting in poor picture quality, and the aggregation of small targets and multiple targets brings difficulties to target recognition. In order to improve the accuracy of marine target detection, the image enhancement and improved YOLOv4 algorithm are used to identify marine organisms. Firstly, aiming at the problems of image blur, some of the images are enhanced with the multi-scale retinex with colour restoration (MSRCR) enhancement algorithm so that the image is clearer and it is easier to extract features. Secondly, Mosaic augmentation is added to YOLOv4 to enrich the data set and increase network robustness. Then the Spatial Pyramid Pooling (SPP) module of YOLOv4 is improved by changing the size of the pooling core, which increases the range of feature extraction and improves the detection capabilities, and its mAP value reaches 97.06%. The experimental results show that the detection accuracy of the image enhancement and improved YOLOv4 algorithm is 7.16% higher than that of the original algorithm. And the improved YOLOv4 algorithm is improved in average precision and recall rate compared with other algorithms, which verifies the effectiveness of the algorithm.
在海洋环境中,存在背景复杂、照度低等问题,导致图像质量差,小目标和多目标的聚集给目标识别带来困难。为了提高海洋目标检测的精度,采用图像增强和改进的YOLOv4算法对海洋生物进行识别。首先,针对图像模糊的问题,对部分图像采用多尺度retinex with colour restoration (MSRCR)增强算法进行增强,使图像更清晰,更容易提取特征;其次,在YOLOv4中加入了马赛克增强,丰富了数据集,提高了网络的鲁棒性。然后通过改变池化核的大小对YOLOv4的空间金字塔池化(SPP)模块进行改进,增加了特征提取的范围,提高了检测能力,其mAP值达到97.06%。实验结果表明,图像增强和改进后的YOLOv4算法的检测精度比原算法提高了7.16%。与其他算法相比,改进后的YOLOv4算法在平均精度和召回率方面都有提高,验证了算法的有效性。
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引用次数: 6
A novel modularized formation tracking control for mixed-order discrete-time multi-agent systems 一种新的混合阶离散多智能体系统模块化编队跟踪控制
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-27 DOI: 10.1080/21642583.2022.2079021
Jun Zhao, Heng-jie Liu, Xingzhong Xiong, Guoping Liu, Hang Yang
A modularized output formation tracking control for mixed-order multi-agent systems is investigated. The multi-agent systems are composed of first-order and second-order integrators. The stability and formation tracking performance are analysed theoretically by the mathematical induction method. Finally, the effectiveness of the proposed modularized output control protocol is verified by simulation examples.
研究了混合阶多智能体系统的模块化输出编队跟踪控制。多智能体系统由一阶和二阶积分器组成。采用数学归纳法对其稳定性和编队跟踪性能进行了理论分析。最后,通过仿真实例验证了所提出的模块化输出控制协议的有效性。
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引用次数: 1
Crop pest recognition based on a modified capsule network 基于改进胶囊网络的作物害虫识别
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-17 DOI: 10.1080/21642583.2022.2074168
Shanwen Zhang, Rongzhi Jing, Xiaoli Shi
Crop pest insects seriously affect yield and quality of crops, and pesticide control methods cause severe environmental pollution, which has inextricably influenced people’s daily lives. Crop pest identification in the field is crucial components of pest control. It is much more complex than generic object recognition due to the apparent differences in the same pest species in the field with various shapes, colours, sizes and complex background. A crop pest recognition method is proposed based on a modified capsule network (MCapsNet). In MCapsNet, a capsule network is used to improve the traditional convolutional neural network (CNN), and an attention module is introduced to capture the most important classification features and speed up the network training. The experimental results on a pest image dataset validate that the proposed method is effective and feasible in classifying various types of insects in field crops and can be implemented in the agriculture sector for crop protection.
农作物病虫害严重影响农作物产量和质量,农药防治方法造成严重的环境污染,对人们的日常生活产生了不可分割的影响。田间作物病虫害识别是病虫害防治的重要组成部分。由于同一害虫种类在不同形状、颜色、大小和复杂背景的田地中存在明显差异,因此它比一般对象识别复杂得多。提出了一种基于改进胶囊网络的作物害虫识别方法。在MCapsNet中,使用胶囊网络来改进传统的卷积神经网络(CNN),并引入注意力模块来捕捉最重要的分类特征并加快网络训练。在害虫图像数据集上的实验结果验证了所提出的方法在田间作物中对各种类型的昆虫进行分类是有效和可行的,并且可以在农业部门实施作物保护。
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引用次数: 3
LSTM-certainty as early warning signal for critical transitions lstm确定性作为关键转变的早期预警信号
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-17 DOI: 10.1080/21642583.2022.2075950
M. Füllsack
We trained a long-short-term-memory (LSTM)-neural network on time series generated with an agent-based model that was designed to differentiate the drivers of its dynamics into external and internal forces, with the internal ones stemming from neighbourhood interaction considered as ‘social’ influence. The trained LSTM proved capable of predicting changes in the dynamics of time series from systems prone to critical transitions. The probability of the assessment – i.e. the ‘certainty’ of the LSTM for its prediction – thus can be used to indicate qualitative changes in a system's behaviour. In many cases, these certainties announce imminent state changes earlier and also more clearly than the set of statistical methods, which is suggested for predicting critical transitions under the term early warning signals.
我们在一个基于代理的模型生成的时间序列上训练了一个长短期记忆(LSTM)神经网络,该模型旨在将其动态的驱动因素区分为外部和内部力量,其中源于邻里互动的内部因素被认为是“社会”影响。经过训练的LSTM被证明能够预测容易发生临界过渡的系统的时间序列动力学变化。评估的概率——也就是LSTM预测的“确定性”——因此可以用来指示系统行为的质变。在许多情况下,这些确定性比一套统计方法更早、更清楚地宣布即将发生的状态变化,后者被建议用于预测预警信号下的关键转变。
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引用次数: 0
A robust control scheme for synchronizing fractional order disturbed chaotic systems with uncertainty and time-varying delay 具有不确定性和时变时滞的分数阶扰动混沌系统同步的鲁棒控制方案
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-13 DOI: 10.1080/21642583.2022.2040059
Hai-Bo Gu, Jianhua Sun, H. Imani
In this paper, a new method is presented for synchronization between two fractional order delayed chaotic systems, while there is uncertainty on the models and external disturbances enter the systems at the same time. The considered delay in the fractional order system is unspecified and varied with time, and of course it is present in different forms in master and slave systems. External disturbances enter the master–slave systems in a finite manner, albeit with an undetermined upper bound, and uncertainty is present in the nonlinear functions of chaotic systems. The goal of synchronizing a particular class of master–slave chaotic systems is achieved through a combination of adaptive and sliding mode techniques. The sliding mode method has been used to cover the effects of uncertainties and delay functions, and an adaptive method has been applied to ensure the stability of the proposed synchronization technique, disturbance upper bound estimation and overcoming the effects of delay variability. A practical example of the innovative method is simulated in MATLAB environment and the obtained results confirm the optimal efficiency of the proposed synchronization method.
针对两个分数阶延迟混沌系统存在不确定性和外部干扰同时存在的情况,提出了一种新的同步方法。分数阶系统中所考虑的延迟是不确定的,并且随时间而变化,当然,它在主从系统中以不同的形式存在。外部干扰以有限的方式进入主从系统,尽管具有不确定的上界,并且混沌系统的非线性函数中存在不确定性。通过自适应和滑模技术的结合,实现了对一类主从混沌系统的同步。采用滑模方法覆盖不确定性和延迟函数的影响,并采用自适应方法确保所提出的同步技术的稳定性、干扰上界估计和克服延迟可变性的影响。在MATLAB环境中对该方法进行了仿真,仿真结果验证了该同步方法的最佳效率。
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引用次数: 0
Recent advances on cooperative control of heterogeneous multi-agent systems subject to constraints: a survey 约束条件下异构多智能体系统协同控制研究进展
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-11 DOI: 10.1080/21642583.2022.2074169
Guang-yu Bao, Lifeng Ma, X. Yi
In this paper, the cooperative control of heterogeneous multi-agent systems (HMASs) subject to certain constraints are surveyed. First, HMASs are classified into two categories, namely, weak and strong HMASs, according to different cooperative behaviours. Then, control strategies are discussed for HMASs when facing different sorts of constraints imposed on the agent dynamics and on the communication networks. Subsequently, some latest results on the cooperative control subject to various kinds of constraints are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out.
本文研究了在一定约束条件下异构多智能体系统的协同控制问题。首先,根据不同的合作行为,HMAS分为两类,即弱HMAS和强HMAS。然后,讨论了HMAS在面临对代理动力学和通信网络施加的不同约束时的控制策略。随后,总结了在各种约束条件下的协同控制的一些最新结果。最后得出结论,并指出了未来可能的研究方向。
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引用次数: 51
Semi-time-dependent stabilization for a class of continuous-time impulsive switched linear systems 一类连续时间脉冲切换线性系统的半时间相关镇定
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-10 DOI: 10.1080/21642583.2022.2074170
Jitai Liang
In this paper, the stability and stabilization problems of a class of impulsive switched linear systems with mode-dependent persistent dwell-time (MPDT) switching are investigated in continuous-time domain. The proposed switching law is more general, which not only covers the widely probed dwell-time (DT) and average dwell-time (ADT) as special cases but also extends the persistent dwell time (PDT) in the literature. By invoking novel modal partition time-dependent multiple Lyapunov-like functions, the stability criteria for the systems under MPDT switching in nonlinear settings are established as a first attempt, upon which the desired mode-dependent and semi-time-dependent (STD) stabilizing controllers for continuous-time impulsive switched linear systems are designed. It is demonstrated that the control performance is improved as both the length of admissible MPDT and the number of time partition segment are added. Finally, a numerical example is provided to illustrate the potential of the obtained theoretical results.
研究了一类具有模相关持续停留时间(MPDT)切换的脉冲切换线性系统在连续时域上的稳定性和镇定问题。所提出的开关律更为普遍,不仅涵盖了广泛探测的停留时间(DT)和平均停留时间(ADT)作为特例,而且扩展了文献中的持续停留时间(PDT)。通过调用新颖的模态划分时变多重类李雅普诺夫函数,首次建立了非线性设置下MPDT切换下系统的稳定性判据,并在此基础上设计了连续时间脉冲切换线性系统的模态相关和半时相关稳定控制器。结果表明,随着可容许MPDT长度和分时段数量的增加,控制性能得到了改善。最后给出了一个数值算例来说明所得理论结果的潜力。
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引用次数: 0
Implementation of sensorless contact force estimation in collaborative robot based on adaptive third-order sliding mode observer 基于自适应三阶滑模观测器的协作机器人无传感器接触力估计的实现
IF 4.1 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2022-05-10 DOI: 10.1080/21642583.2022.2063201
Quang Dan Le, Hee-Jun Kang
In this paper, we propose the estimation of contact force in a collaborative robot without explicit force-sensing based on the adaptive third-order sliding mode observer. An adaptive third-order sliding mode observer was designed to estimate the contact force based only on the position measurement. The information from the observer was used for admittance control and emergent stop control when the robot interacts with a human. The experimental results with the emergent stop control and admittance control, using the proposed contact force estimation for the 3-DOF AT2-FARA robot manipulator, illustrate the capability of the proposed system in real-world application.
在本文中,我们提出了一种基于自适应三阶滑模观测器的无显式力传感协作机器人接触力估计方法。设计了一种自适应三阶滑模观测器,仅基于位置测量来估计接触力。当机器人与人交互时,来自观测器的信息被用于准入控制和紧急停止控制。使用所提出的三自由度AT2-FARA机器人机械手接触力估计,对紧急停止控制和导纳控制的实验结果表明了所提出的系统在实际应用中的能力。
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引用次数: 2
期刊
Systems Science & Control Engineering
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