{"title":"基于粒子群算法的四旋翼飞行器高度控制PID优化","authors":"Jack Connor, M. Seyedmahmoudian, B. Horan","doi":"10.1109/AUPEC.2017.8282423","DOIUrl":null,"url":null,"abstract":"The proportional-integral-derivate (PID) controller has been relied on by control engineers due to its easy implementation and good performance. Although PID controllers are readily available, they still have limitations. Tuning these controllers often require a deep understanding of control theory to adjust their parameters correctly, which is often time consuming and may not result in an optimal performance. In this study, the use of particle swarm optimization (PSO) is proposed to improve a PID controller on a quadrotor. The PID controller is used to control the height of the quadrotor. Moreover, a simulation run in MATLAB is constructed to increase the height of the quadrotor from 0 m to 1 m. The PSO algorithm is used to tune the controller against a cost function that considers the squared error, maximum overshoot, and the integral of absolute error, which are used to evaluate the performance of the PID values. The PSO should converge on a global minimum, which will be the optimal values of the PID controller. Results from the simulation reveal the performance of the PSO algorithm and the efficiency of the PID controller compared with other methods.","PeriodicalId":155608,"journal":{"name":"2017 Australasian Universities Power Engineering Conference (AUPEC)","volume":"333 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Using particle swarm optimization for PID optimization for altitude control on a quadrotor\",\"authors\":\"Jack Connor, M. Seyedmahmoudian, B. Horan\",\"doi\":\"10.1109/AUPEC.2017.8282423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proportional-integral-derivate (PID) controller has been relied on by control engineers due to its easy implementation and good performance. Although PID controllers are readily available, they still have limitations. Tuning these controllers often require a deep understanding of control theory to adjust their parameters correctly, which is often time consuming and may not result in an optimal performance. In this study, the use of particle swarm optimization (PSO) is proposed to improve a PID controller on a quadrotor. The PID controller is used to control the height of the quadrotor. Moreover, a simulation run in MATLAB is constructed to increase the height of the quadrotor from 0 m to 1 m. The PSO algorithm is used to tune the controller against a cost function that considers the squared error, maximum overshoot, and the integral of absolute error, which are used to evaluate the performance of the PID values. The PSO should converge on a global minimum, which will be the optimal values of the PID controller. Results from the simulation reveal the performance of the PSO algorithm and the efficiency of the PID controller compared with other methods.\",\"PeriodicalId\":155608,\"journal\":{\"name\":\"2017 Australasian Universities Power Engineering Conference (AUPEC)\",\"volume\":\"333 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Australasian Universities Power Engineering Conference (AUPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUPEC.2017.8282423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Australasian Universities Power Engineering Conference (AUPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUPEC.2017.8282423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using particle swarm optimization for PID optimization for altitude control on a quadrotor
The proportional-integral-derivate (PID) controller has been relied on by control engineers due to its easy implementation and good performance. Although PID controllers are readily available, they still have limitations. Tuning these controllers often require a deep understanding of control theory to adjust their parameters correctly, which is often time consuming and may not result in an optimal performance. In this study, the use of particle swarm optimization (PSO) is proposed to improve a PID controller on a quadrotor. The PID controller is used to control the height of the quadrotor. Moreover, a simulation run in MATLAB is constructed to increase the height of the quadrotor from 0 m to 1 m. The PSO algorithm is used to tune the controller against a cost function that considers the squared error, maximum overshoot, and the integral of absolute error, which are used to evaluate the performance of the PID values. The PSO should converge on a global minimum, which will be the optimal values of the PID controller. Results from the simulation reveal the performance of the PSO algorithm and the efficiency of the PID controller compared with other methods.