Pub Date : 2013-10-01DOI: 10.1109/APUAVD.2013.6705320
M. Komnatska
A contemporary approach of flight control system design via static output feedback design is proposed. The static output feedback is formulated in terms of linear matrix inequalities. The obtained solution guarantees stabilization of unmanned aerial vehicle (UAV) during flight mission. During flight envelope the unmanned aerial vehicle is subjected to the external stochastic disturbances. The efficiency of the proposed approach is illustrated by a case study of UAV longitudinal motion.
{"title":"Flight control system design via static output feedback: LMI-approach","authors":"M. Komnatska","doi":"10.1109/APUAVD.2013.6705320","DOIUrl":"https://doi.org/10.1109/APUAVD.2013.6705320","url":null,"abstract":"A contemporary approach of flight control system design via static output feedback design is proposed. The static output feedback is formulated in terms of linear matrix inequalities. The obtained solution guarantees stabilization of unmanned aerial vehicle (UAV) during flight mission. During flight envelope the unmanned aerial vehicle is subjected to the external stochastic disturbances. The efficiency of the proposed approach is illustrated by a case study of UAV longitudinal motion.","PeriodicalId":400843,"journal":{"name":"2013 IEEE 2nd International Conference Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121871833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-01DOI: 10.1109/APUAVD.2013.6705303
I. Rataichuk, V. Kortunov
INS errors present one of the major problems in development of navigation systems for aerial vehicles. This problem is especially actual for Mini and Micro UAVs where INS is based on MEMS which possesses high spectral density noise and instability. Another problem for Micro UAVs is restrictions applied for onboard hardware. Autopilots designed for this UAVs utilizes microcontrollers for CPU, which executes functions of flight control, navigation system, payload control and etc. So one needs simple and reliable algorithm for errors compensation in this particular types of autopilots. Existing algorithms, such as Complementary Filters or Kalman Filter, already are used in INS and performs very well. But there is always a way for improvements. Such improvement is a Luenberger Observer. It can estimate navigation and sensors errors. This algorithm is simpler, thus faster, than Kalman Filter. In this paper implementation of Luenberger Observer in Attitude and Heading Reference System (AHRS) (specific type of INS) is considered. The simulation of algorithm performance using real onboard data and feasibility of its implementation in navigation systems is shown.
{"title":"INS errors compensation algorithm based on Luenberger Observer","authors":"I. Rataichuk, V. Kortunov","doi":"10.1109/APUAVD.2013.6705303","DOIUrl":"https://doi.org/10.1109/APUAVD.2013.6705303","url":null,"abstract":"INS errors present one of the major problems in development of navigation systems for aerial vehicles. This problem is especially actual for Mini and Micro UAVs where INS is based on MEMS which possesses high spectral density noise and instability. Another problem for Micro UAVs is restrictions applied for onboard hardware. Autopilots designed for this UAVs utilizes microcontrollers for CPU, which executes functions of flight control, navigation system, payload control and etc. So one needs simple and reliable algorithm for errors compensation in this particular types of autopilots. Existing algorithms, such as Complementary Filters or Kalman Filter, already are used in INS and performs very well. But there is always a way for improvements. Such improvement is a Luenberger Observer. It can estimate navigation and sensors errors. This algorithm is simpler, thus faster, than Kalman Filter. In this paper implementation of Luenberger Observer in Attitude and Heading Reference System (AHRS) (specific type of INS) is considered. The simulation of algorithm performance using real onboard data and feasibility of its implementation in navigation systems is shown.","PeriodicalId":400843,"journal":{"name":"2013 IEEE 2nd International Conference Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121584876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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