{"title":"基于后退地平线控制的运载火箭上升制导","authors":"Qianwei He, Ye Yang, Lei Liu, Zhongtao Cheng","doi":"10.23919/CCC50068.2020.9188647","DOIUrl":null,"url":null,"abstract":"For the difficulties and challenges caused by the unknown disturbance during the ascent stage of the launch vehicle, a trajectory tracking strategy using particle swarm optimization (PSO) algorithm in a receding horizon control (RHC) framework is investigated in this paper. Since the RHC solves the online optimization problem at each step, the calculations can be time-consuming. To speed up the computation of RHC, the online optimization problem is transformed into a one-dimensional variable optimal problem and the control actions are obtained by PSO. Providing solve times in milliseconds, which guarantees the feasibility of the RHC controller. Simulation results are provided to illustrate that this strategy can not only satisfy the fast calculation speed, but also can realize better performance with the existence of aerodynamic uncertainty, thrust uncertainty, and process constraint.","PeriodicalId":255872,"journal":{"name":"2020 39th Chinese Control Conference (CCC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ascent Guidance for Launch Vehicle Based on Receding Horizon Control\",\"authors\":\"Qianwei He, Ye Yang, Lei Liu, Zhongtao Cheng\",\"doi\":\"10.23919/CCC50068.2020.9188647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the difficulties and challenges caused by the unknown disturbance during the ascent stage of the launch vehicle, a trajectory tracking strategy using particle swarm optimization (PSO) algorithm in a receding horizon control (RHC) framework is investigated in this paper. Since the RHC solves the online optimization problem at each step, the calculations can be time-consuming. To speed up the computation of RHC, the online optimization problem is transformed into a one-dimensional variable optimal problem and the control actions are obtained by PSO. Providing solve times in milliseconds, which guarantees the feasibility of the RHC controller. Simulation results are provided to illustrate that this strategy can not only satisfy the fast calculation speed, but also can realize better performance with the existence of aerodynamic uncertainty, thrust uncertainty, and process constraint.\",\"PeriodicalId\":255872,\"journal\":{\"name\":\"2020 39th Chinese Control Conference (CCC)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 39th Chinese Control Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CCC50068.2020.9188647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 39th Chinese Control Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CCC50068.2020.9188647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ascent Guidance for Launch Vehicle Based on Receding Horizon Control
For the difficulties and challenges caused by the unknown disturbance during the ascent stage of the launch vehicle, a trajectory tracking strategy using particle swarm optimization (PSO) algorithm in a receding horizon control (RHC) framework is investigated in this paper. Since the RHC solves the online optimization problem at each step, the calculations can be time-consuming. To speed up the computation of RHC, the online optimization problem is transformed into a one-dimensional variable optimal problem and the control actions are obtained by PSO. Providing solve times in milliseconds, which guarantees the feasibility of the RHC controller. Simulation results are provided to illustrate that this strategy can not only satisfy the fast calculation speed, but also can realize better performance with the existence of aerodynamic uncertainty, thrust uncertainty, and process constraint.