2019 7th International Conference on Control, Mechatronics and Automation (ICCMA)最新文献_第5页

Automated Smart Home Controller Based on Adaptive Linear Neural Network 基于自适应线性神经网络的自动化智能家居控制器

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988733

Puji Catur Siswipraptini, Rosida Nur Aziza, Iriansyah B. M. Sangadji, Indrianto Indrianto, R. Siregar

{"title":"Automated Smart Home Controller Based on Adaptive Linear Neural Network","authors":"Puji Catur Siswipraptini, Rosida Nur Aziza, Iriansyah B. M. Sangadji, Indrianto Indrianto, R. Siregar","doi":"10.1109/ICCMA46720.2019.8988733","DOIUrl":"https://doi.org/10.1109/ICCMA46720.2019.8988733","url":null,"abstract":"The purpose of this research is to model a smart home appliances control system using a neural network method. This control system consists of several components i.e. rain sensor, temperature sensor, light sensor, stepper motor and LCD on Arduino. Adaptive linear neural networks called Adaline algorithm is used for the training process of artificial neural networks. The inputs and targets are trained with a network that has been built to get the learning weights to be used as the basis for calculations on the next incoming training data. Adaline algorithm is used for the training process of Artificial Neural Networks. The results of the output of light intensity are 0, 150, 300, 400 with lux units and the results of the intensity of rain are 0, 250, 400, 700 in mm units of each water humidity simulated in light and rain sensors. The input obtained will be processed into an output that will move the motor to the position that has been set. Contribution of the results of this study, a proposed neural network-based multi-control system model based on criteria values of Adaline.","PeriodicalId":377212,"journal":{"name":"2019 7th International Conference on Control, Mechatronics and Automation (ICCMA)","volume":"54 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125304389","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: 6

Observer Design for Boundary Coupled Fractional Order Distributed Parameter Systems 边界耦合分数阶分布参数系统观测器设计

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988754

Yanjiu Zhou, Juan Chen, B. Cui

引用次数: 2

Towards the Automation of a Chemical Sulphonation Process with Machine Learning 用机器学习实现化学磺化过程的自动化

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988752

Enrique Garcia-Ceja, Åsmund Hugo, Brice Morin, Per Olav Hansen, E. Martinsen, An Ngoc Lam, Øystein Haugen

{"title":"Towards the Automation of a Chemical Sulphonation Process with Machine Learning","authors":"Enrique Garcia-Ceja, Åsmund Hugo, Brice Morin, Per Olav Hansen, E. Martinsen, An Ngoc Lam, Øystein Haugen","doi":"10.1109/ICCMA46720.2019.8988752","DOIUrl":"https://doi.org/10.1109/ICCMA46720.2019.8988752","url":null,"abstract":"Nowadays, the continuous improvement and automation of industrial processes has become a key factor in many fields, and in the chemical industry, it is no exception. This translates into a more efficient use of resources, reduced production time, output of higher quality and reduced waste. Given the complexity of today’s industrial processes, it becomes infeasible to monitor and optimize them without the use of information technologies and analytics. In recent years, machine learning methods have been used to automate processes and provide decision support. All of this, based on analyzing large amounts of data generated in a continuous manner. In this paper, we present the results of applying machine learning methods during a chemical sulphonation process with the objective of automating the product quality analysis which currently is performed manually. We used data from process parameters to train different models including Random Forest, Neural Network and linear regression in order to predict product quality values. Our experiments showed that it is possible to predict those product quality values with good accuracy, thus, having the potential to reduce time. Specifically, the best results were obtained with Random Forest with a mean absolute error of 0.089 and a correlation of 0.978.","PeriodicalId":377212,"journal":{"name":"2019 7th International Conference on Control, Mechatronics and Automation (ICCMA)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134227664","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: 3

Equilibrium Formulation of a 3-DOF Compliant Mechanism using Sylvester’s Dialytic Method of Elimination 用Sylvester的透析消去法求解三自由度柔顺机构的平衡公式

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988715

Mustafa M. Mustafa, C. Crane, I. Hamad

{"title":"Equilibrium Formulation of a 3-DOF Compliant Mechanism using Sylvester’s Dialytic Method of Elimination","authors":"Mustafa M. Mustafa, C. Crane, I. Hamad","doi":"10.1109/ICCMA46720.2019.8988715","DOIUrl":"https://doi.org/10.1109/ICCMA46720.2019.8988715","url":null,"abstract":"This paper studies the equilibrium formulation of a three degree of freedom planar compliant platform mechanism, which is in contact with a solid body in its environment. The mechanism includes two platforms, which are connected in parallel by three linear springs. The capability of deformation by manipulating both platforms exceptionally complicates the problem. The analysis aims to determine all equilibrium configurations for two different cases: FIRST CASE all three springs have zero free lengths and SECOND CASE only two of the springs have zero free lengths. The proposed procedure calculates the pose of the top platform when it is not in contact with the surface, and then detects if the top platform is in contact to determine the equilibrium configurations. To solve the geometric equations of the mechanism, we use Sylvester’s method of elimination. The approach obtains 4th and 48th-degree polynomial equations for the first and second cases, respectively. Numerical examples have been applied to verify the process of analysis. The results, which are numerically calculated by software Maple, prove the validity of the analysis.","PeriodicalId":377212,"journal":{"name":"2019 7th International Conference on Control, Mechatronics and Automation (ICCMA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133075263","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

Adaptive Backstepping Control of a 2-DOF Helicopter 二自由度直升机的自适应反演控制

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988761

S. Schlanbusch, Jing Zhou

引用次数: 4

Mango Classification System Based on Machine Vision and Artificial Intelligence 基于机器视觉和人工智能的芒果分类系统

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988603

Nguyen Truong Thinh, Nguyen Duc Thong, Huynh Thanh Cong, Nguyen Tran Thanh Phong

{"title":"Mango Classification System Based on Machine Vision and Artificial Intelligence","authors":"Nguyen Truong Thinh, Nguyen Duc Thong, Huynh Thanh Cong, Nguyen Tran Thanh Phong","doi":"10.1109/ICCMA46720.2019.8988603","DOIUrl":"https://doi.org/10.1109/ICCMA46720.2019.8988603","url":null,"abstract":"Sorting and Classification of mango, there are different colors, weights, sizes, shapes and densities. Currently, classification based on the above features is being carried out mainly by manuals due to farmers’ awareness of low accuracy, high costs, health effects and high costs, costly economically inferior. The internal quality of the mango such as sweetness, hardness, age, brittleness… is very important but is only estimated by external or human-perceived evaluation. Therefore, it is necessary to use artificial neural networks to solve this problem. This study was conducted on three main commercial mango species of Vietnam to find out the method of classification of mango with the best quality and accuracy. World studies of mango classification according to color, size, volume and almost done in the laboratory but not yet applied in practice. The quality assessment of mango fruit has not been resolved. Application of image processing technology, computer vision combined with artificial intelligence in the problem of mango classification or poor quality. The goal of the study is to create a system that can classify mangoes in terms of color, volume, size, shape and fruit density. The classification system using image processing incorporates artificial intelligence including the use of CCD cameras, C language programming, computer vision and artificial neural networks. The system uses the captured mango image, processing the split layer to determine the mass, volume and defect on the mango fruit surface. Especially, determine the density of mangoes related to its maturity and sweetness and determine the percentage of mango defects to determine the quality of mangoes for export and domestic or recycled mangoes.","PeriodicalId":377212,"journal":{"name":"2019 7th International Conference on Control, Mechatronics and Automation (ICCMA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128399058","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: 7

Path Planning for Multiple Mobile Robots in Smart Warehouse 智能仓库中多移动机器人的路径规划

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988635

Ali Bolu, Ömer Korçak

引用次数: 15

Flushing Pressure Automation for Efficient Machining in EDM Process 电火花加工中高效加工的冲洗压力自动化

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988592

T. Muthuramalingam, S. Vasanth, L. G. Babu, D. Saravanakumar, P. Karthikeyan

引用次数: 2

ICCMA 2019 Committees

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/iccma46720.2019.8988741

引用次数: 0

An Error Correction Approach based on AR model and RLS for Inertial Navigation System 基于AR模型和RLS的惯性导航系统误差校正方法

2019 7th International Conference on Control, Mechatronics and Automation (ICCMA) Pub Date : 2019-11-01 DOI: 10.1109/ICCMA46720.2019.8988615

Di Wang, Xiaosu Xu, Yongyun Zhu

引用次数: 0