{"title":"利用模糊控制器为无人驾驶飞行器建立高木-菅野(T-S)模糊模型","authors":"Muhammad Shamrooz Aslam , Hazrat Bilal","doi":"10.1016/j.asej.2024.102984","DOIUrl":null,"url":null,"abstract":"<div><p>Drone technology has the potential to disrupt and augment our quality of life, as it is rapidly growing in popularity and being utilized in various applications, such as agriculture, emergency response, border control, asset inspection, and intelligent transportation. On the other side, Artificial intelligent instruments that possess a variety of input and output (I/O) mechanisms are employed to achieve model stabilizing with data estimation. Firstly, in the present study, a linear mathematical model was developed for a quad–copter Unmanned Aerial Vehicle (UAV), in which the Takagi–Sugeno (T–S) Fuzzy logic framework was integrated. The crisp variables have been used to make the interference between the input and output of the T–S fuzzy system. Secondly, to control a quadcopter model with inherent dynamic instability, these state space models are crucial. Inputs of fuzzy controller are data generated by sensors and Bluetooth connected to IoT. The state–space model of the quad copter, which consists of six Degrees Of Freedom (6–DOF), is derived by utilizing fundamental Newtonian equations. This establishment of the model holds significant value in effectively governing the quad copter system. Thirdly, the system stabilizing has been proved by linear matrix inequalities (LMIs) with an associated Lyapunov function with the <em>γ</em> performance index. Simulation results have been presented to demonstrate the efficiency of our proposed algorithm with additional computational burden analysis.</p></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2090447924003599/pdfft?md5=6c95f8f2b0102617559c4449edc1ac44&pid=1-s2.0-S2090447924003599-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Modeling a Takagi-Sugeno (T-S) fuzzy for unmanned aircraft vehicle using fuzzy controller\",\"authors\":\"Muhammad Shamrooz Aslam , Hazrat Bilal\",\"doi\":\"10.1016/j.asej.2024.102984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Drone technology has the potential to disrupt and augment our quality of life, as it is rapidly growing in popularity and being utilized in various applications, such as agriculture, emergency response, border control, asset inspection, and intelligent transportation. On the other side, Artificial intelligent instruments that possess a variety of input and output (I/O) mechanisms are employed to achieve model stabilizing with data estimation. Firstly, in the present study, a linear mathematical model was developed for a quad–copter Unmanned Aerial Vehicle (UAV), in which the Takagi–Sugeno (T–S) Fuzzy logic framework was integrated. The crisp variables have been used to make the interference between the input and output of the T–S fuzzy system. Secondly, to control a quadcopter model with inherent dynamic instability, these state space models are crucial. Inputs of fuzzy controller are data generated by sensors and Bluetooth connected to IoT. The state–space model of the quad copter, which consists of six Degrees Of Freedom (6–DOF), is derived by utilizing fundamental Newtonian equations. This establishment of the model holds significant value in effectively governing the quad copter system. Thirdly, the system stabilizing has been proved by linear matrix inequalities (LMIs) with an associated Lyapunov function with the <em>γ</em> performance index. Simulation results have been presented to demonstrate the efficiency of our proposed algorithm with additional computational burden analysis.</p></div>\",\"PeriodicalId\":48648,\"journal\":{\"name\":\"Ain Shams Engineering Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2090447924003599/pdfft?md5=6c95f8f2b0102617559c4449edc1ac44&pid=1-s2.0-S2090447924003599-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ain Shams Engineering Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2090447924003599\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447924003599","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Modeling a Takagi-Sugeno (T-S) fuzzy for unmanned aircraft vehicle using fuzzy controller
Drone technology has the potential to disrupt and augment our quality of life, as it is rapidly growing in popularity and being utilized in various applications, such as agriculture, emergency response, border control, asset inspection, and intelligent transportation. On the other side, Artificial intelligent instruments that possess a variety of input and output (I/O) mechanisms are employed to achieve model stabilizing with data estimation. Firstly, in the present study, a linear mathematical model was developed for a quad–copter Unmanned Aerial Vehicle (UAV), in which the Takagi–Sugeno (T–S) Fuzzy logic framework was integrated. The crisp variables have been used to make the interference between the input and output of the T–S fuzzy system. Secondly, to control a quadcopter model with inherent dynamic instability, these state space models are crucial. Inputs of fuzzy controller are data generated by sensors and Bluetooth connected to IoT. The state–space model of the quad copter, which consists of six Degrees Of Freedom (6–DOF), is derived by utilizing fundamental Newtonian equations. This establishment of the model holds significant value in effectively governing the quad copter system. Thirdly, the system stabilizing has been proved by linear matrix inequalities (LMIs) with an associated Lyapunov function with the γ performance index. Simulation results have been presented to demonstrate the efficiency of our proposed algorithm with additional computational burden analysis.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.