Automation, Control and Intelligent Systems最新文献

New Findings in the Stability Analysis of PI-state Controlled Systems with Actuator Saturation 致动器饱和 PI 状态控制系统稳定性分析的新发现

Automation, Control and Intelligent Systems Pub Date : 2024-04-12 DOI: 10.11648/j.acis.20241201.11

Uwe Nuss

{"title":"New Findings in the Stability Analysis of PI-state Controlled Systems with Actuator Saturation","authors":"Uwe Nuss","doi":"10.11648/j.acis.20241201.11","DOIUrl":"https://doi.org/10.11648/j.acis.20241201.11","url":null,"abstract":"In this paper, a simple, generally valid stability proof for an anti-windup method for PI-state controlled systems is presented, with which it is possible to directly conclude the stability of the PI-state controlled system from a stable P-state controlled system with constraints in the manipulated variables, i.e. without having to perform a separate stability investigation of the anti-windup measures. The technique presented is based on the system description by means of state equations and Lyapunov's Direct Method using quadratic Lyapunov functions. Furthermore, the PI-state controller is designed in such a way that it provides the same command response as the P-state controller, for which a stability statement is already available. Both continuous-time and discrete-time systems are considered, which, apart from the saturation of the manipulated variables, show linear, time-invariant behavior. In addition, a general stability proof is given for discrete-time systems, which makes it possible to establish stable anti-windup methods for P- and PI-state controlled systems, which contain dead time elements in the path of the manipulated variables, without having to carry out separate stability investigations for them. For this purpose, the state controller design for the system with dead time elements in the manipulated variable paths is based on the principle that the same characteristics of the control behavior should be achieved as for the system without such dead time elements, but delayed by the dead time. The effectiveness of the presented methods is illustrated by an example from the field of electrical drives.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"8 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140712094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design GUI App on MATLAB for Comparison Analysis of LQR and Pole Placement Controller for Speed Control DC Motor 在 MATLAB 上设计 GUI 应用程序，用于对用于速度控制直流电机的 LQR 和极点布局控制器进行比较分析

Automation, Control and Intelligent Systems Pub Date : 2023-10-30 DOI: 10.11648/j.acis.20231103.11

Alemie Assefa

引用次数: 0

Towards a Bijective Co-simulation Model Between Physical and Virtual Environments, Adapted to a Platform for Autonomous Industrial Vehicles 面向自动驾驶工业车辆平台的物理与虚拟环境双向联合仿真模型

Automation, Control and Intelligent Systems Pub Date : 2023-07-11 DOI: 10.11648/j.acis.20231102.12

M. Djoko-Kouam, A. Fougères

引用次数: 0

LED Display System Characterisation Based on Wireless Communication Techniques: A Systematic Review 基于无线通信技术的LED显示系统特性研究

Automation, Control and Intelligent Systems Pub Date : 2023-07-06 DOI: 10.11648/j.acis.20231102.11

Isaac Collins Febaide, Akpofure A. Enughwure

引用次数: 0

Prospects and Challenges of Large Language Models in the Field of Intelligent Building 大型语言模型在智能建筑领域的前景与挑战

Automation, Control and Intelligent Systems Pub Date : 2023-05-18 DOI: 10.11648/j.acis.20231101.13

Wu Yang, Junjie Wang, Wei-Han Li

{"title":"Prospects and Challenges of Large Language Models in the Field of Intelligent Building","authors":"Wu Yang, Junjie Wang, Wei-Han Li","doi":"10.11648/j.acis.20231101.13","DOIUrl":"https://doi.org/10.11648/j.acis.20231101.13","url":null,"abstract":": At the end of November 2022, the ChatGPT released by OpenAI Inc. performed excellently and quickly became popular worldwide. Despite some shortcomings, Large Language Models (LLM) represented by Generative Pre-trained Transformer (GPT) is here to stay, leading the way for the new generation of Natural Language Processing (NLP) technique. This commentary presents the potential benefits and challenges of the applications of large language models, from the viewpoint of intelligent building. We briefly discuss the history and current state of large language models and their shortcomings. We then highlight how these models can be used to improve the daily maintenance of intelligent building. With regard to challenges, we address some vital problems to be solved before deployment and argue that large language models in intelligent building require maintenance staff to develop sets of competencies and literacies necessary to both understand the technology as well as the maintenance and maneuver of intelligent building. In addition, a clear strategy within intelligent building troops with a strong focus on AI talents construction and training dataset annotation are required to integrate and take full advantage of large language models in the daily maintenance. We conclude with recommendations for how to address these challenges and prepare for further applications of LLM in the field of intelligent building in the future.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115369836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing a Robust Emergency Information System for Natural Disasters 建立健全的自然灾害应急信息系统

Automation, Control and Intelligent Systems Pub Date : 2023-03-16 DOI: 10.11648/j.acis.20231101.12

K. Papatheodosiou, C. Angeli

{"title":"Developing a Robust Emergency Information System for Natural Disasters","authors":"K. Papatheodosiou, C. Angeli","doi":"10.11648/j.acis.20231101.12","DOIUrl":"https://doi.org/10.11648/j.acis.20231101.12","url":null,"abstract":": A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called \" LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124566321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification and Detection of Cabbage Leaf Diseases from Images Using Deep Learning Methods 基于深度学习方法的白菜叶片病害图像分类与检测

Automation, Control and Intelligent Systems Pub Date : 2023-03-04 DOI: 10.11648/j.acis.20231101.11

M. A. N., M. K, R. H. S., Yuktha D. Jain

引用次数: 1

Optimization, Power Management and Reliability Evaluation of Hybrid Wind-PV-Diesel-Battery System for Rural Electrification 农村电气化风电-光伏-柴油-电池混合系统优化、电源管理及可靠性评估

Automation, Control and Intelligent Systems Pub Date : 2021-08-18 DOI: 10.11648/J.ACIS.20210903.11

A. Yahiaoui, A. Tlemçani, A. Kouzou

{"title":"Optimization, Power Management and Reliability Evaluation of Hybrid Wind-PV-Diesel-Battery System for Rural Electrification","authors":"A. Yahiaoui, A. Tlemçani, A. Kouzou","doi":"10.11648/J.ACIS.20210903.11","DOIUrl":"https://doi.org/10.11648/J.ACIS.20210903.11","url":null,"abstract":"Photovoltaic and wind energy are the most promising as a future energy technology and can be classified as a clean sources of electric energy in the world. Size optimization of the hybrid renewable energy system play an important role in minimizing the total cost of the system (TCS) and suitable load supply. The main focus of this research is to develop the efficient approach for the optimization of hybrid renewable energy system composed by photovoltaic area, wind turbine (WT), diesel generator (DG) and battery bank (BB). For this purpose, this paper proposes a new metaheuristic technique called modified grey wolf optimizer (M-GWO) for minimize the TCS of the hybrid system considering power balanced between the components. The study of reliability with loss power supply probability (LPSP), the energy not supplied (ENS) and the reliability of the power supply (RPS) methods are demonstrated. For improving the high exploration and exploitation to find the global optimum and robustness of our new approach the obtained results by M-GWO are compared with Grey Wolf Optimizer (GWO) and particle swarm optimization (PSO) methods.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124690768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Validating Clocking Subsystem in Post Silicon Environment 后硅环境下时钟子系统的验证

Automation, Control and Intelligent Systems Pub Date : 2021-07-13 DOI: 10.11648/J.ACIS.20210902.12

Atulesh Kansal, Himanshu Aggarwal

{"title":"Validating Clocking Subsystem in Post Silicon Environment","authors":"Atulesh Kansal, Himanshu Aggarwal","doi":"10.11648/J.ACIS.20210902.12","DOIUrl":"https://doi.org/10.11648/J.ACIS.20210902.12","url":null,"abstract":"With tremendous growth of automotive and consumer market, demand of semiconductors is also growing. Every new day comes up with a new micro-controller with upgraded feature set. As the feature set is increasing, so is the complexity of the devices. This increased complexity majorly impacts the clocking and power sub system of a micro controller. In this paper, we will talk about clocking sub-system that is also known as HEART of any micro controller. To have a healthy heart of a micro controller, there should be robust testing of micro controller under various conditions. In a multiple clocking domain architecture, there are major issues of SoC getting stuck or wrong clock output. Sometimes, clock can get glitchy due to extreme weather conditions as well. It can also malfunction due to wrong configurations or a marginal configuration. So, to rule out all this kind of issues, randomization, sweeps, testing under different process, voltage and thermal conditions plays an important role. Though it is never possible to cover all the combinations during bench validation of these complex SoC, but in this paper, we have tried to capture some type of tests that can be performed to test the robustness of a micro controller.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"374 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123484102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Face Recognition Algorithm Based on Improved Residual Neural Network 基于改进残差神经网络的人脸识别算法研究

Automation, Control and Intelligent Systems Pub Date : 2021-04-12 DOI: 10.11648/J.ACIS.20210901.16

Tang Xiaolin, W. Xiaogang, Hou Jin, Han Yiting, Huang Ye

{"title":"Research on Face Recognition Algorithm Based on Improved Residual Neural Network","authors":"Tang Xiaolin, W. Xiaogang, Hou Jin, Han Yiting, Huang Ye","doi":"10.11648/J.ACIS.20210901.16","DOIUrl":"https://doi.org/10.11648/J.ACIS.20210901.16","url":null,"abstract":"The residual neural network is prone to two problems when it is used in the process of face recognition: the first is \"overfitting\", and the other is the slow or non-convergence problem of the loss function of the network in the later stage of training. In this paper, in order to solve the problem of \"overfitting\", this paper increases the number of training samples by adding Gaussian noise and salt and pepper noise to the original image to achieve the purpose of enhancing the data, and then we added \"dropout\" to the network, which can improve the generalization ability of the network. In addition, we have improved the loss function and optimization algorithm of the network. After analyzing the three loss functions of Softmax, center, and triplet, we consider their advantages and disadvantages, and propose a joint loss function. Then, for the optimization algorithm that is widely used through the network at present, that is the Adam algorithm, although its convergence speed is relatively fast, but the convergence results are not necessarily satisfactory. According to the characteristics of the sample iteration of the convolutional neural network during the training process, in this paper, the memory factor and momentum ideas are introduced into the Adam optimization algorithm. This can increase the speed of network convergence and improve the effect of convergence. Finally, this paper conducted simulation experiments on the data-enhanced ORL face database and Yale face database, which proved the feasibility of the method proposed in this paper. Finally, this paper compares the time-consuming and power consumption of network training before and after the improvement on the CMU_PIE database, and comprehensively analyzes their performance.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115160204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1