{"title":"基于智能手机的飞行控制器快速模型预测控制","authors":"Luis García, Alejandro Astudillo, Esteban Rosero","doi":"10.1109/CCAC.2019.8920998","DOIUrl":null,"url":null,"abstract":"Several attempts have been made to execute control of a system using only a smartphone’s processor running computationally inexpensive algorithms such as PID, LQR or H∞ controllers. This paper presents design and implementation of model predictive controllers on a smartphone using the numerical optimization framework CasADi. To evaluate this framework’s performance (and compare its results with those from a Java library JOptimizer’s deployment) the implemented model predictive control algorithm was subjected to simulations of running a quadrotor control system on a smartphone. It attained a tracking error of 0.0693 m. These evaluation results open the possibility of implementing more computationally expensive algorithms on a smartphone’s processor including online or real-time usage.","PeriodicalId":184764,"journal":{"name":"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fast Model Predictive Control on a Smartphone-based Flight Controller\",\"authors\":\"Luis García, Alejandro Astudillo, Esteban Rosero\",\"doi\":\"10.1109/CCAC.2019.8920998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several attempts have been made to execute control of a system using only a smartphone’s processor running computationally inexpensive algorithms such as PID, LQR or H∞ controllers. This paper presents design and implementation of model predictive controllers on a smartphone using the numerical optimization framework CasADi. To evaluate this framework’s performance (and compare its results with those from a Java library JOptimizer’s deployment) the implemented model predictive control algorithm was subjected to simulations of running a quadrotor control system on a smartphone. It attained a tracking error of 0.0693 m. These evaluation results open the possibility of implementing more computationally expensive algorithms on a smartphone’s processor including online or real-time usage.\",\"PeriodicalId\":184764,\"journal\":{\"name\":\"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCAC.2019.8920998\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCAC.2019.8920998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Model Predictive Control on a Smartphone-based Flight Controller
Several attempts have been made to execute control of a system using only a smartphone’s processor running computationally inexpensive algorithms such as PID, LQR or H∞ controllers. This paper presents design and implementation of model predictive controllers on a smartphone using the numerical optimization framework CasADi. To evaluate this framework’s performance (and compare its results with those from a Java library JOptimizer’s deployment) the implemented model predictive control algorithm was subjected to simulations of running a quadrotor control system on a smartphone. It attained a tracking error of 0.0693 m. These evaluation results open the possibility of implementing more computationally expensive algorithms on a smartphone’s processor including online or real-time usage.