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Research on short-term power load forecasting based on Elman neural network with Genetic Algorithm 基于遗传算法的Elman神经网络短期电力负荷预测研究
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055581
Yijie Sun, Huiwen Xia
The electric power industry is closely related to the development of national economy. With the development of economy, the social electricity situation is increasingly complicated, which brings great test to the prediction of electric load system. Accurate short-term power load forecasting plays an important role in production scheduling and safe and stable operation of power system. In this paper, Elman neural network based on genetic algorithm is established and a short-term power load forecasting model is established. The actual history data of municipal power grid are simulated, the experimental results show that compared with the BP neural network and Elman neural network commonly, Elman neural network based on genetic algorithm to solve the problem of random initial weights of the Elman neural network, can effectively enhance the power load forecasting accuracy and meet the needs of the actual production and work.
电力工业与国民经济的发展密切相关。随着经济的发展,社会用电形势日益复杂,给电力负荷系统的预测带来了很大的考验。准确的短期电力负荷预测对生产调度和电力系统安全稳定运行具有重要作用。本文建立了基于遗传算法的Elman神经网络,建立了短期电力负荷预测模型。对市政电网的实际历史数据进行了仿真,实验结果表明,与常用的BP神经网络和Elman神经网络相比,Elman神经网络基于遗传算法解决了Elman神经网络初始权值随机的问题,能够有效提高电力负荷预测的精度,满足实际生产和工作的需要。
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引用次数: 0
A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators 一类移动机械臂的内点法轨迹跟踪算法
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055380
Xuechen Rao, Yahui Gan, Xiaoteng Wang
At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm.
目前,由于移动机械臂系统具有高冗余度和强耦合的特点,对其协调运动规划的研究较少,但研究深入。针对上述问题,本文提出了一种基于一类五自由度移动机械臂的末端执行器期望轨迹跟踪的协调控制算法。该算法以整个系统的功耗和轨迹稳定性为优化目标,将所选优化目标的函数设置在期望的轨迹上,并基于凸优化的内点法进行优化,以更快地收敛到最优解。最后对系统进行了仿真,验证了控制算法的正确性和有效性。
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引用次数: 0
Safety behavior detection of factory workers based on multi task model 基于多任务模型的工厂工人安全行为检测
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055311
Hui Wang, Guanzheng Tan, Degang Xu
This paper focuses on the safety problems in the industrial production process. Through the investigation of copper processing plant, we found that workers have little safety awareness, who often get into factories without helmets and enter non-safety areas without permission. To prevent safety accidents, we propose a multi-task model to detect some unsafe behaviors based on computer vision techniques. The model is composed of a shared encoder and two independent decoder branches. It can be used to detect the safety helmet and the factory landmark lines at the same time. According to the detection results, it can be judged whether the workers regularly wear the safety helmet or they are in the unsafe area in real time. Through the judgment of workers’ safety status, we can strengthen the safety supervision of industrial site, which has strong practical significance and application prospect.
本文主要研究工业生产过程中的安全问题。通过对铜加工厂的调查,我们发现工人的安全意识不强,经常不戴安全帽进入工厂,未经允许进入非安全区域。为了防止安全事故的发生,我们提出了一种基于计算机视觉技术的多任务模型来检测一些不安全行为。该模型由一个共享的编码器和两个独立的解码器分支组成。可同时检测安全帽和工厂地标线。根据检测结果,可以实时判断工人是否定期佩戴安全帽或处于不安全区域。通过对工人安全状况的判断,加强对工业现场的安全监管,具有较强的现实意义和应用前景。
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引用次数: 0
Robust identification of input nonlinear block structure systems 输入非线性块结构系统的鲁棒辨识
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055932
Shi-Du Dong, Yuzhu Zhang, Jiawei Liu, Xingxing Zhou, Xuesong Wang
A robust identification algorithm is presented for nonlinear systems with disturbance, which is fitted by Hammerstein block structure model. A hierarchical least squares method is proposed to estimate model parameters and track disturbance in combination with auxiliary modelling strategies and separable techniques. The multi-innovation technology for error updating is used to augment the dimension of the innovation matrix, in order to reduce the estimation error variance and enhance the convergence stability of the algorithm. The time-varying disturbance is still tracking by a single innovation strategy. Two adaptive forgetting factors are proposed to enhance the system parameters' convergence characteristics and to improve the track ability of time-varying disturbance. An example is applied to validate the benefits of the proposed algorithm. The established model can facilitate controller design and system operation monitoring.
提出了一种用Hammerstein块结构模型拟合具有扰动的非线性系统的鲁棒辨识算法。结合辅助建模策略和可分离技术,提出了一种层次最小二乘法来估计模型参数和跟踪扰动。采用多创新技术进行误差更新,增加创新矩阵的维数,以减小估计误差方差,提高算法的收敛稳定性。时变扰动仍然被单一的创新策略所跟踪。提出了两个自适应遗忘因子,增强了系统参数的收敛特性,提高了对时变扰动的跟踪能力。通过算例验证了该算法的有效性。所建立的模型便于控制器设计和系统运行监控。
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引用次数: 0
Intelligent Assignment Strategy for Multi-Target Adversarial Interception 多目标对抗拦截的智能分配策略
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10054926
Yang Yu, Yizhong Fang, Han Wu, Tuo Han, Q. Hu
The multi-missile confront multi-target is a classic target allocation issue in the combat scenario of multiple missiles intercepting multiple maneuvering targets. Traditional algorithms lack environmental assessment model, train quality, and indicator function in the adversarial environment. To this end, this paper aims to propose an intelligent assignment strategy which contains indicator function and evaluation model. Then, an indicator function and an evaluation model considering the miss distance, threat situation, and the number of specified interception targets are introduced into the reinforcement learning algorithm. The local and global reward functions are introduced to improve the training convergence and efficiency in the multi-missile multi-target confrontation scenario. Finally, simulation results are designed to check on advantage of intelligent allocation strategy.
多弹对抗多目标是多弹拦截多机动目标作战场景中的典型目标分配问题。传统算法缺乏对抗环境下的环境评价模型、训练质量和指标功能。为此,本文提出了一种包含指标函数和评价模型的智能分配策略。然后,在强化学习算法中引入了考虑脱靶量、威胁情况和指定拦截目标数量的指标函数和评估模型;为了提高多导弹多目标对抗场景下训练的收敛性和效率,引入了局部和全局奖励函数。最后,设计了仿真结果,验证了智能分配策略的优越性。
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引用次数: 0
Dynamic Analysis of Service-oriented Advanced Avionics System based on Stochastic Evolutionary Game 基于随机进化博弈的服务型先进航电系统动态分析
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10054905
Zhaohui Liu, Qingchun Liu, Bingfei Li, Shuo Zhang
Service-oriented advanced avionics system(SOAAS) is a complex network system with different stakeholders. Stake-holders are irrational behavior and may take aberrant behaviors in advanced avionics system. Different behavior will lead the avionics system to different states. In order to accurately predict the development trend of SOAAS and grasp its dynamic characteristics, stochastic evolutionary game theory is applied to study and analyze SOAAS in this paper. A multi-party game model is constructed to describe the behaviours of participant, and Ito stochastic differential equation is established based on stochastic theory to break through the limitation of replicator dynamics equation. The stability problem of SOAAS is effectively analyzed, and sufficient conditions of system stability are given. Simulation results show the correct and practicable of the established game model and analysis method.
面向服务的先进航空电子系统(SOAAS)是一个具有不同利益相关者的复杂网络系统。在先进航电系统中,利益相关者是一种非理性行为,可能会出现异常行为。不同的行为会导致航电系统进入不同的状态。为了准确预测SOAAS的发展趋势,掌握其动态特征,本文运用随机进化博弈论对SOAAS进行研究和分析。构建了描述参与者行为的多方博弈模型,并基于随机理论建立了伊藤随机微分方程,突破了复制因子动力学方程的局限性。有效地分析了soa系统的稳定性问题,给出了系统稳定的充分条件。仿真结果表明所建立的博弈模型和分析方法是正确可行的。
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引用次数: 0
Optimized PI Control with Tracking Differentiator for Negative Pressure Cabin Control 带跟踪微分器的优化PI控制负压座舱控制
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10056016
H. Ren, Cui-Cui Song
To block the epidemics like "Corona Virus Disease 2019(COVID-19)" spreading, an effective isolation of the infected patients during the transportation is an important issue, which makes the negative pressure cabin (NPC) become a key equipment. There exist some practical NPCs in service, whose pressures are mostly controlled using the conventional PID controller with parameters regulated by engineering methods. Until now, there is no report about the model of NPC system from the authors’ best knowledge. In this paper, the model of the NPC system is reported, which is an inherent nonlinear system. Because of the nonlinear nature of the cabin pressure, the conventional PID controller cannot achieve desire performance to balance the transient and the steady state performance, even though the optimized PID parameters are chosen using the on-line optimization based on genetic algorithm. To solve such a problem, Tracking Differentiator (TD) and PI controller are combined to achieve the desire performance using the optimized parameters. The experiment results show the improvement of the proposed method.
为了阻断“2019冠状病毒病”(COVID-19)等疫情的传播,在运输过程中有效隔离感染者是一个重要问题,这使得负压舱(NPC)成为关键设备。目前在役的一些实际npc,其压力控制多采用传统的PID控制器,参数采用工程方法调节。到目前为止,据作者所知还没有关于NPC系统模型的报道。本文报道了NPC系统的模型,它是一个固有的非线性系统。由于客舱压力的非线性特性,传统的PID控制器即使采用基于遗传算法的在线优化方法选择优化后的PID参数,也无法达到平衡稳态和瞬态性能的理想效果。为了解决这一问题,将跟踪微分器(TD)与PI控制器相结合,利用优化后的参数实现理想的性能。实验结果表明了该方法的改进。
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引用次数: 0
Multi-scale Traffic Sign Detection and Recognition Method Fused with Attention Mechanism 融合注意机制的多尺度交通标志检测与识别方法
Pub Date : 2022-11-25 DOI: 10.1109/cac57257.2022.10055690
Changjiang Jiang, Zixuan Huang, Li Tan, Xiaoming Luo
For the problems of the traditional methods in the process of small target detection of traffic signs, such as being susceptible to environmental factors, poor real-time performance and weak generalization ability, this paper proposes an improved road traffic sign detection and recognition method based on YOLOv5 target detection model. Firstly, the original target box in YOLOv5 network which was not suitable for this detection task is improved, and the clustering method of target box obtained from the original network was optimized to K-Means++ clustering method to generate new anchor coordinates. Secondly, the CSP structure of YOLOv5 network was replaced by the CSPGhost structure composed of Ghost module. The CBAM attention mechanism module is added behind the backbone network to improve the image feature extraction ability of the network model. Finally, the detection layer structure of the model is improved, and the detection scale of the target is increased to improve the detection accuracy of the model for small targets. In order to verify the effectiveness of the improved network, a model comparison experiment is designed in this paper. It shows that 45 types of traffic signs are detected on TT100K traffic sign dataset. The experimental results show that the accuracy of the improved network is improved by 7.26% compared with YOLOv5 network.
针对传统方法在交通标志小目标检测过程中易受环境因素影响、实时性差、泛化能力弱等问题,本文提出了一种基于YOLOv5目标检测模型的改进道路交通标志检测识别方法。首先,对YOLOv5网络中不适合本检测任务的原始目标盒进行改进,将原始网络中得到的目标盒聚类方法优化为k - means++聚类方法,生成新的锚点坐标;其次,将YOLOv5网络的CSP结构替换为由Ghost模块组成的CSPGhost结构。在骨干网后面加入CBAM注意机制模块,提高网络模型的图像特征提取能力。最后,改进了模型的检测层结构,增加了目标的检测尺度,提高了模型对小目标的检测精度。为了验证改进后的网络的有效性,本文设计了模型对比实验。结果表明,在TT100K交通标志数据集上检测到45种交通标志。实验结果表明,与YOLOv5网络相比,改进后的网络准确率提高了7.26%。
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引用次数: 0
Research on Energy Management Optimization Strategy of Integrated Energy System in Wind Photovoltaic Hydrogen Energy Storage Area 风电光伏储氢区综合能源系统能量管理优化策略研究
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055600
T. Shi, Chang Xu, Xiangpeng Xie, Wenhao Dong, Chun-sheng Tang
This paper mainly studies the energy management optimization strategy of regional integrated energy including hydrogen storage under the condition of renewable energy access. In this paper, an energy management optimization strategy of integrated energy system for scenic hydrogen storage area is proposed. The strategy aims at minimizing the comprehensive electricity cost in the region within a certain period of time, and considers diversified distributed power sources and load types such as wind power generation, photovoltaic power generation, hydrogen power generation, hydrogen energy storage, battery energy storage, electric boiler and interruptible load. As a example the paper takes a regional renewable energy system to analyze, and the results show that the strategy can fully exploit the consumption space of renewable energy generation, maximize the local consumption of renewable energy generation, and minimize the power generation cost of integrated energy system, which has certain practical application significance.
本文主要研究可再生能源接入条件下包括储氢在内的区域一体化能源管理优化策略。提出了一种风景式储氢区综合能源系统的能量管理优化策略。该战略以在一定时间内使区域内综合电力成本最小化为目标,考虑风力发电、光伏发电、氢能发电、氢能储能、电池储能、电锅炉、可中断负荷等多种分布式电源和负荷类型。本文以某区域可再生能源系统为例进行分析,结果表明,该策略能够充分挖掘可再生能源发电的消费空间,使可再生能源发电的局部消费最大化,使综合能源系统的发电成本最小化,具有一定的实际应用意义。
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引用次数: 0
Single Machine Control for Energy Consumption Analysis in Bernoulli Serial Lines 伯努利串联生产线的单机控制能耗分析
Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10054874
Xiuxuan Tian, Zhiyang Jia, Zunjun Wang, Yongsheng Qi
The green development of the manufacturing is supported by energy conservation and environmental protection policies. The implementation of strategies has gradually expanded from a single field to multiple fields. These changes improve quality of products, innovation ability and efficiency of resource allocation of manufacturing systems. In recent years, reducing energy consumption has become the focus of both industry and academics. In order to save energy, we consider switching on/off a machine in the production lines when certain thresholds of buffers are reached. In this paper, we investigate Bernoulli serial lines with buffers having limited capacity which run finite production. Mathematical model of the three-machine line which produce finite products is established and analytical methods of calculating production rate, consumption rate, blocking probability, starvation probability, completion time and energy consumption are proposed. Markovian approach is adopted in three-machine lines analysis. Meanwhile, simulation is used to analyse serial lines that have numerous machines.
制造业的绿色发展得到了节能环保政策的支持。战略的实施从单一领域逐渐扩展到多个领域。这些变化提高了制造系统的产品质量、创新能力和资源配置效率。近年来,降低能源消耗已成为工业界和学术界关注的焦点。为了节约能源,我们考虑在达到某些缓冲阈值时打开/关闭生产线中的机器。本文研究了具有有限产量的有限容量缓冲器的伯努利系列生产线。建立了有限产品三机生产线的数学模型,提出了计算生产率、消耗率、阻塞概率、饥饿概率、完成时间和能耗的分析方法。三机线分析采用马尔可夫方法。同时,对具有多台机器的串行生产线进行仿真分析。
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引用次数: 0
期刊
2022 China Automation Congress (CAC)
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