{"title":"Kinematic Implementation of 3-DOF 2-Link Type Vehicle Simulator : Kinematic analysis and motion control method for 3-DOF 2-link type vehicle simulator","authors":"Donggyu Kim, Sung-Ho Hwang","doi":"10.1109/ICCAD49821.2020.9260532","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260532","url":null,"abstract":"The vehicle simulator aims to provide the user with a driving experience that reproduces the sensations experienced in a real vehicle. The important thing is to duplicate the motion. Therefore various parallel manipulator have been developed like six and three degree of freedom motion platform(vehicle simulator). In this paper, we present kinematic analysis of a manipulator with new type of 2-link structure and motion cueing through inverse kinematics. For accurate calculation, Matlab and a recursive method was used.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126993670","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}
{"title":"Autonomous Landing of UAV on Moving Platform: A Mathematical Approach","authors":"Morteza Alijani, Anas Osman","doi":"10.1109/ICCAD49821.2020.9260498","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260498","url":null,"abstract":"Recently, the demand for Unmanned Aerial Vehicles (UAVs) has substantially escalated amidst the current unprecedented events and the global pandemic, as they play an essential role in both the security and health sectors, through surveillance, extracting and conveying test samples, transportation of crucial assets and providing temporary services. Nevertheless, the process of designing and producing such aerial vehicles is suppressed by the internal and external constraints that pose serious challenges. One of the key operations during flight is landing, especially, the autonomous landing of UAV on a moving platform, which is a scientifically complicated engineering problem. Typically, executing a successful automatic landing on a moving platform requires accurate localization of the landing zone, swift flying trajectory planning, and robust control configuration. To accomplish such goals, intense observations of the data concerning the autonomous landing approach such as the intersection point between the two moving bodies, the position of the platform/UAV and the inclination angle required to land are significantly crucial. In this paper, a mathematical approach to this problem is presented in the X-Y plane based on the inclination angle and state of UAV during the landing procedure. Moreover, the experimental results depict the accurate position of the UAV, the intersection between the UAV and the moving platform and inclination angle in the landing process, allowing for prediction of the intersection point.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127658123","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}
{"title":"Implementation of an Advanced PEM Hydrogen Storage System Based Cogeneration Using Photovoltaic System in a Building","authors":"Moulebe Laince Pierre, Touati Abdelwahed, Rabbah Nabila","doi":"10.1109/ICCAD49821.2020.9260552","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260552","url":null,"abstract":"The development of renewable energies in the world continues to increase due to the growing demand for energy in emerging and developing economies. Encouraging, the tertiary sector and manufacturers constantly to use them. However, the injection of these energies into the electrical networks is a source of problems due to the instability of the renewable energies production, this generates serious penalties. One of the solutions to this production instability is the use of storage systems, moreover the fight against CO2 is a primordial challenge of our time. It is recommended to set up a clean storage system like that of the hydrogen produced by the electrolysis of water called Proton Exchange Membrane (PEM). On the other hand, implementation of this technique must provide an economic investment for the system. In this work, we describe the modeling and simulation of a photovoltaic system producing hydrogen by electrolysis of water (PEM), intended to supply the electrical and thermal loads of a building, where thermal energy is supplied by a solar thermal collector. The stored hydrogen is used to recharge fuel cells to maintain energy production in the network or for self-consumption. Knowing that the heating energy consumption is important. In this study we aim to improve energy efficiency through cogeneration on the thermal contribution of a building by using a system of heat recovery by electrolysis of water to heat a floor for example and thus reduce the energy bills and therefore implicitly the cost of PEM storage. The Analysis and simulation results using MATLAB/Simulink confirm the effectiveness and performances of the proposed technique.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134370525","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}
Amin Mechernene, Vincent Judalet, A. Chaibet, M. Boukhnifer
{"title":"Risk Analysis Method for a Lane Change Maneuvers on Highways","authors":"Amin Mechernene, Vincent Judalet, A. Chaibet, M. Boukhnifer","doi":"10.1109/ICCAD49821.2020.9260515","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260515","url":null,"abstract":"One important aspect of decision making algorithms for the autonomous driving is to behave like a human driver for two main reasons: to be understandable by the other road users, and not to cause discomfort to passengers. To this end, it is necessary to understand how the driver asses risk while driving. In this work, a risk assessment method is proposed inspired by human drivers and specific to lane changing maneuvers. For this contribution, a MOOVE dataset is used, a proprietary dataset of the VEDECOM institute. The primary assumption is that for a given lane changing maneuver, the maneuver is a less dangerous with a more samples performed in riskier situations in the dataset. The purpose of this work consists of developing a decision algorithm based on the proposed risk analysis method to decide whether a lane change maneuver should be made and how.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130409563","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}
{"title":"A Review on Intelligent Predictive Maintenance: Bibliometric analysis and new research directions","authors":"V. Grubisic, J. F. Aguiar, Z. Simeu-Abazi","doi":"10.1109/ICCAD49821.2020.9260504","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260504","url":null,"abstract":"Industry 4.0 has brought a number of new technologies that are completely changing the shape of today’s maintenance processes. However, studies about these new technologies are still premature. This article provides an understanding and analysis of the most current and relevant studies on the area. As a method, we first selected the most relevant articles using a bibliometric methodology called the Theory of the Consolidated Meta-analytic Approach (TEMAC) method, then the 13 most significant studies were reviewed and presented and finally a study of possible gaps in the literature left uncovered by authors that allowed us to identify key elements and to forecast the future of Intelligent Predictive Maintenance.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122632150","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}
{"title":"A new Signal Processing-based Prognostic Approach applied to Turbofan Engines","authors":"Khaoula Tidriri, Sylvain Verron, Nizar Chatti","doi":"10.1109/ICCAD49821.2020.9260547","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260547","url":null,"abstract":"For modern engineering industry, Prognostic has become a key feature in maintenance strategies since it enables to enhance system availability and safety while reducing operational costs and avoiding unscheduled maintenance. Prognostic can be seen as the prediction of the system’s remaining useful life with the purpose of minimizing catastrophic failure events. Such task could be performed on the basis of an accurate physical representation of the system behavior and/or by using available historical data that have been collected.In this paper, a novel prognostic approach is proposed, based on data-driven category techniques. This approach uses mainly historical data, regardless of the underlying physical process, and it can be divided into two steps. First, an original signal processing technique is used to develop life prediction models. In the second step, the system’s current health state is predicted and the RUL is estimated based on a proposed formula. This approach is validated by using four different data sets generated from the NASA’s turbofan engine simulator (C-MAPSS) and the obtained results are compared with relevant existing approaches tested using the same collected data. The main outputs of our study attest that the proposed approach is robust, applicable and effective even in the presence of various fault modes and operating conditions.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122981816","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}
Jhon Charaja, E. Munoz-Panduro, O. E. Ramos, Ruth Canahuire
{"title":"Trajectory Tracking Control of UR5 Robot: a PD with Gravity Compensation and Sliding Mode Control Comparison","authors":"Jhon Charaja, E. Munoz-Panduro, O. E. Ramos, Ruth Canahuire","doi":"10.1109/ICCAD49821.2020.9260559","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260559","url":null,"abstract":"Good trajectory tracking and fast convergence are critical characteristics on medical and industrial applications. This behavior must be ensured despite the presence of disturbances to successfully complete the task. This work presents the design and robustness comparison of two control approaches computationally implemented on UR5 robot for trajectory tracking. The control methods that will be compared are proportional-derivative control with gravity compensation and sliding mode control. Both control methods will be designed to ensure stability and good tracking of circular helicoidal trajectory on the operational space. In order to evaluate the robustness of both control methods, a controlled white-noise signal will be added to robot model. The obtained results indicate that sliding mode control deals better with external disturbances than proportional-derivative control with gravity compensation.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124337797","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}
{"title":"Dual Control of Linear Discrete-Time Systems with Time-Varying Parameters","authors":"Christian Rosdahl, B. Bernhardsson","doi":"10.1109/ICCAD49821.2020.9260540","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260540","url":null,"abstract":"We describe how the optimal dual controller for a discrete-time linear system can be found by approximately solving the corresponding Bellman equation using a neural network to represent the value function. We illustrate the method on an example with time-varying dynamics, where the new method is shown to give improved performance.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"104 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120972149","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}
{"title":"Trajectory Optimization for An Autonomous Vehicle Driving across Stochastic Traffic Flows based on Direct Collocation","authors":"Yuwei Sun, Russ Tedrake, H. Ochiai","doi":"10.1109/ICCAD49821.2020.9260494","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260494","url":null,"abstract":"Trajectory optimization is widely adopted in the control of autonomous vehicles, allowing them to drive on a road without collisions with obstacles and other vehicles on the road. However, different from the scenario of driving along a road, manipulating an autonomous vehicle to cross a road shows more challenges to solving the optimization problem. In this research, we adopt a method called direction collocation for solving this nonconvex trajectory optimization problem, where the goal of the autonomous vehicle is to drive across traffic flows from one side of the road to the other side, with randomly localized vehicles in four lanes coming in both directions. We present the dynamics of the autonomous vehicle as well as other vehicles on the road. Then we add constraints including no collisions, speed limit, and torque limit, adopting the fuel consumption as the cost. At last, we use direct collocation to compute the optimized trajectory with various traffic flow rates. It shows great robustness for the scheme to find the optimized solution with stochastic traffic flows.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"665 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116099970","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}
Marwa Fradi, Mouna Afif, El-Hadi Zahzeh, K. Bouallegue, Mohsen Machhout
{"title":"Transfer-Deep Learning Application for Ultrasonic Computed Tomographic Image Classification","authors":"Marwa Fradi, Mouna Afif, El-Hadi Zahzeh, K. Bouallegue, Mohsen Machhout","doi":"10.1109/ICCAD49821.2020.9260569","DOIUrl":"https://doi.org/10.1109/ICCAD49821.2020.9260569","url":null,"abstract":"Deep-learning techniques have led to a technological progress in several fields such as robotics, mechanics, and medicine specifically in the area of medical imaging. On the light of these recent developments in deep learning it will be recorded that medical imaging evolution needs a transfer deep learning application for the classification process. In this paper, our approach consists on a deep learning transfer models such us Inception V3, MobileNet, NasNet and Ameobanet on Ultrasonic Computed tomography images (USCT) to classify them automatically into three classes. In the beginning, USCT dataset augmentation has been done with pre-processing algorithms. Then, a Transfer Convolutional Neural Network Architecture has been applied with different models on our dataset. Finally, we have implemented our neural network application on GPU. As results we have overcoming previously works by a value of 100% for train accuracy and a value of 96% for test accuracy with a short time process.","PeriodicalId":270320,"journal":{"name":"2020 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123267358","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}