2022 8th International Conference on Control, Instrumentation and Automation (ICCIA)最新文献

Robust Fuzzy Observer-Based Speed Control of Electric Vehicle with Unmeasurable Premise Variables 基于鲁棒模糊观测器的不可测前提变量电动汽车速度控制

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737171

Z. Echreshavi, M. Shasadeghi, M. H. Asemani

引用次数: 1

A Typical Skill 4.0 Platform for Process Safety Management 工艺安全管理的典型技能4.0平台

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737170

R. Mokhtarname, A. Safavi, Leonhard Urbas, F. Salimi, H. Taghipour

引用次数: 0

Forecasting the Condition Severity of COVID-19 in Terms of Prevalence in Iran 根据伊朗流行情况预测COVID-19病情严重程度

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737177

M. Hajji, Ahmad Ali Rafiee, A. Safavi, Mahmoud Farhang

{"title":"Forecasting the Condition Severity of COVID-19 in Terms of Prevalence in Iran","authors":"M. Hajji, Ahmad Ali Rafiee, A. Safavi, Mahmoud Farhang","doi":"10.1109/ICCIA54998.2022.9737177","DOIUrl":"https://doi.org/10.1109/ICCIA54998.2022.9737177","url":null,"abstract":"Since the advent of the Coronavirus disease 2019 (COVID-19) pandemic, one of the most significant attempts toward coping with this disease was predicting the severity condition of this pandemic in terms of prevalence. In this way, the authorities can make better and more informative decisions. Machine Learning has great potential to solve such data-driven problems. In this article, the issue of predicting the future COVID-19 prevalence severity as a classification task has been investigated. We employed four state-of-the-art predictive models, Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Self-Attention mechanism, in order to predict the COVID-19 prevalence severity in Iran using the gathered dataset by Johns Hopkins University. The main challenge we have faced was data scarcity because of the limited duration of the pandemic. Besides, as we are considering a classification task, data imbalance was an issue due to imposing a conventional criterion to divide each day into three classes regarding the state of severity. The final results suggest that although the performance of all models was acceptable, Self-Attention with an accuracy of 95% was the superb architecture to deal with this classification task.","PeriodicalId":382149,"journal":{"name":"2022 8th International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540522","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

Self-powered WiFi-connected monitoring stations for environmental pollution app-based control in urban and industrial areas 自供电的wifi连接监测站，用于城市和工业区的环境污染应用程序控制

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737209

Paolo Visconti, R. de Fazio, R. Velázquez, B. Al-Naami, A. A. Ghavifekr

引用次数: 0

An Artificial Bee Colony Based PID Controller for Depth Control of an Autonomous Underwater Vehicle 基于人工蜂群PID的自主水下机器人深度控制

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737208

Kouhyar Sheida, M. Nobari, Barmak Baigzadehnoe, H. Bevrani

引用次数: 0

An Intelligent Gearbox Fault Diagnosis under Different Operating Conditions using Adversarial Domain Adaptation 基于对抗域自适应的齿轮箱不同工况智能故障诊断

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737160

M. Kavianpour, Mohammadreza Ghorvei, Parisa Kavianpour, Amin Ramezani, Mohammad T. H. Beheshti

{"title":"An Intelligent Gearbox Fault Diagnosis under Different Operating Conditions using Adversarial Domain Adaptation","authors":"M. Kavianpour, Mohammadreza Ghorvei, Parisa Kavianpour, Amin Ramezani, Mohammad T. H. Beheshti","doi":"10.1109/ICCIA54998.2022.9737160","DOIUrl":"https://doi.org/10.1109/ICCIA54998.2022.9737160","url":null,"abstract":"Effective gearbox diagnostic procedures can assist in rotary machinery's reliable and safe operation. On the other hand, the constant change in operational conditions, along with an absence of labeled data, have made fault diagnosis difficult. Changes in working conditions that cause discrepancies in data distribution and a lack of labeled data dramatically reduce fault diagnosis accuracy in deep learning algorithms. In recent years, unsupervised domain adaptation (UDA) has been utilized to overcome these challenges in various applications. This paper introduces a new approach based on the CNN model and hybrid domain adaptation called deep coral adversarial network (DCAN) to solve these issues. The CNN model is used to extract features, and the distribution discrepancy between domains is decreased by applying two modules of domain adversarial learning and deep coral adaptation. The proposed method's performance was evaluated using the SEU gearbox dataset. The results demonstrate the proposed method's proper performance in diagnosing gearbox faults under different operating conditions.","PeriodicalId":382149,"journal":{"name":"2022 8th International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"337 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127436437","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

Designing and simulation of an automatic control system for an underwater vehicle 水下航行器自动控制系统设计与仿真

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737189

M. Keshtkar, S. Kavari, Iman Fakharian, Javad Zare Ehteshami

{"title":"Designing and simulation of an automatic control system for an underwater vehicle","authors":"M. Keshtkar, S. Kavari, Iman Fakharian, Javad Zare Ehteshami","doi":"10.1109/ICCIA54998.2022.9737189","DOIUrl":"https://doi.org/10.1109/ICCIA54998.2022.9737189","url":null,"abstract":"The purpose of this paper is to linearize given non-linear differential equations and design a complete automatic control system for the vertical and horizontal motions of an underwater vehicle like submarine using a steady state decoupling scheme. The method of solution is linearizing the DSL (Dynamic Language Simulation) non-linear equations of motion by assumption of constant axial velocity and negligible non-linear terms. So, the degree of freedom is reduced from 6 to 5. Static and hydrodynamics stability derivatives are calculated by using reference method analytically and are compared with reference results. In order to validate linearized model with specified initial conditions, results using MATLAB Simulink software are obtained and compared with non-linear model of reference. After obtaining valid linear models, results of designed PID automatic controller in depth and course are compared with results of Lead-Lag controller of reference. It is concluded that fluctuations and undershoots are not captured in PID in horizontal motion. Also, steady state error in PID controller is less than Lead-Lag controller in vertical motion.","PeriodicalId":382149,"journal":{"name":"2022 8th International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127444284","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

Synthetic to Real Framework based on Convolutional Multi-Head Attention and Hybrid Domain Alignment 基于卷积多头注意和混合域对齐的实数框架合成

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737184

Mohammadreza Ghorvei, M. Kavianpour, Mohammad T. H. Beheshti, Amin Ramezani

{"title":"Synthetic to Real Framework based on Convolutional Multi-Head Attention and Hybrid Domain Alignment","authors":"Mohammadreza Ghorvei, M. Kavianpour, Mohammad T. H. Beheshti, Amin Ramezani","doi":"10.1109/ICCIA54998.2022.9737184","DOIUrl":"https://doi.org/10.1109/ICCIA54998.2022.9737184","url":null,"abstract":"Domain adaptation (DA) has obtained remarkable results in unsupervised fault diagnosis methods. However, its performance is highly related to two significant factors: Firstly, proposed DA methods should alleviate the global and local distribution gap to precisely matching all distributions in the source and target domain. Most distance-based DA methods assume global DA or concentrate only on local aligning distributions on the country. Secondly, the generalization of most proposed unsupervised fault diagnosis methods relies on labeled faulty data collected from sensors. Contrarily, collected data in real-world scenarios are mostly unlabeled, which considerably declines the model's generalization. We proposed an unsupervised synthetic to the real framework to overcome two significant challenges. A convolution multi-head attention network based on hybrid multi-layer domain alignment (CMHA-HMLDA) is conducted to align global and local distributions. It also alleviates the gap between real and synthetic data more accurately to maintain a robust data-driven model for bearing fault diagnosis. Furthermore, the proposed method is reliable in real scenarios because of transferring employed knowledge of labeled synthetic data into unlabeled real data. To show the supervisory of our proposed method in diagnosing unlabeled real health states, we validated it with a synthetic dataset made from the benchmark bearing Case Western Reserve University (CWRU) dataset. We compared it with recently published unsupervised fault diagnosis methods. Consequently, we achieved state-of-art results that show our proposed method is capable of realizing unlabeled real bearing faults from synthetic data, and it is practical in real-world scenarios.","PeriodicalId":382149,"journal":{"name":"2022 8th International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122899825","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: 5

Trotting Gait Planning and Modeling of a Quadruped Robot 四足机器人小跑步态规划与建模

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737167

Ardalan Aeini, Mohammadhossein Pourassad, M. Haghjoo, M. Taghizadeh

引用次数: 3

Design of a Nonlinear Backstepping Versus Sliding Mode Controller for a Human Musculoskeletal arm Model in Sagittal plane 矢状面人体肌肉骨骼臂模型非线性反步反滑模控制器的设计

2022 8th International Conference on Control, Instrumentation and Automation (ICCIA) Pub Date : 2022-03-02 DOI: 10.1109/ICCIA54998.2022.9737172

B. Saeedi, Milad Alizadeh, M. Moghaddam, Majid Sadedel

引用次数: 0