{"title":"用于电动汽车(EV)直流(DC)电机 PIηDλ 控制器数值模拟的分数排序亚当斯-巴什福斯-穆尔顿(FABM)方法","authors":"Aashima Bangia , Rashmi Bhardwaj","doi":"10.1016/j.rico.2024.100466","DOIUrl":null,"url":null,"abstract":"<div><div>The model for the speed control in the Direct Current (DC) motors by developing different simulating models based upon Proportional Integral Derivative (PID) controllers with fractional-ordered Adams–Bashforth–Moulton (ABM) method has been developed. With the aim of more efficient insights, a general closed loop in PID type controllers have been constructed alongwith their implementation. PID control system consists of rule-set essential to monitor the different parameters of the environment. The control of mechanisms through Fractional-order controls (FOC) in real life applications require techniques that would build controllers; tune parameters for accurate and precise monitoring. It is known that PID controllers are sensitive to uncertainties which arise from imprecise knowledge of the kinematics and dynamics therefore an adaptive fractional PID (AFPID) controller has been proposed to use the robustness of fractional-ordered controller. In previous works, FPID controller parameters are constant during control process but in this study these parameters will be updated online with an adequate adaptation mechanism to have better results. Outcomes found to be consistent between represent a step towards understanding the relation between chaotic phenomena and fractional calculus. It has been observed that the <span><math><mrow><mi>P</mi><msup><mrow><mi>I</mi></mrow><mrow><mi>η</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>λ</mi></mrow></msup></mrow></math></span> control dynamics can boost the controllers’ performance by increase of tuning knobs. In addition, the initialization and execution time have decreased substantially from 2.64 to 0.87 secs and 0.5 to 0.15 secs.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100466"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fractional-ordered Adams–Bashforth–Moulton (FABM) method for PIηDλ controllers’ numerical simulations for Direct Current (DC) motors in Electric Vehicles (EVs)\",\"authors\":\"Aashima Bangia , Rashmi Bhardwaj\",\"doi\":\"10.1016/j.rico.2024.100466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The model for the speed control in the Direct Current (DC) motors by developing different simulating models based upon Proportional Integral Derivative (PID) controllers with fractional-ordered Adams–Bashforth–Moulton (ABM) method has been developed. With the aim of more efficient insights, a general closed loop in PID type controllers have been constructed alongwith their implementation. PID control system consists of rule-set essential to monitor the different parameters of the environment. The control of mechanisms through Fractional-order controls (FOC) in real life applications require techniques that would build controllers; tune parameters for accurate and precise monitoring. It is known that PID controllers are sensitive to uncertainties which arise from imprecise knowledge of the kinematics and dynamics therefore an adaptive fractional PID (AFPID) controller has been proposed to use the robustness of fractional-ordered controller. In previous works, FPID controller parameters are constant during control process but in this study these parameters will be updated online with an adequate adaptation mechanism to have better results. Outcomes found to be consistent between represent a step towards understanding the relation between chaotic phenomena and fractional calculus. It has been observed that the <span><math><mrow><mi>P</mi><msup><mrow><mi>I</mi></mrow><mrow><mi>η</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>λ</mi></mrow></msup></mrow></math></span> control dynamics can boost the controllers’ performance by increase of tuning knobs. In addition, the initialization and execution time have decreased substantially from 2.64 to 0.87 secs and 0.5 to 0.15 secs.</div></div>\",\"PeriodicalId\":34733,\"journal\":{\"name\":\"Results in Control and Optimization\",\"volume\":\"17 \",\"pages\":\"Article 100466\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Results in Control and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666720724000961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Control and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666720724000961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Fractional-ordered Adams–Bashforth–Moulton (FABM) method for PIηDλ controllers’ numerical simulations for Direct Current (DC) motors in Electric Vehicles (EVs)
The model for the speed control in the Direct Current (DC) motors by developing different simulating models based upon Proportional Integral Derivative (PID) controllers with fractional-ordered Adams–Bashforth–Moulton (ABM) method has been developed. With the aim of more efficient insights, a general closed loop in PID type controllers have been constructed alongwith their implementation. PID control system consists of rule-set essential to monitor the different parameters of the environment. The control of mechanisms through Fractional-order controls (FOC) in real life applications require techniques that would build controllers; tune parameters for accurate and precise monitoring. It is known that PID controllers are sensitive to uncertainties which arise from imprecise knowledge of the kinematics and dynamics therefore an adaptive fractional PID (AFPID) controller has been proposed to use the robustness of fractional-ordered controller. In previous works, FPID controller parameters are constant during control process but in this study these parameters will be updated online with an adequate adaptation mechanism to have better results. Outcomes found to be consistent between represent a step towards understanding the relation between chaotic phenomena and fractional calculus. It has been observed that the control dynamics can boost the controllers’ performance by increase of tuning knobs. In addition, the initialization and execution time have decreased substantially from 2.64 to 0.87 secs and 0.5 to 0.15 secs.