When a helicopter is flying, the dynamics vary depending on, for example, speed and position. Hence, a time-invariant linear model cannot describe its properties under all flight conditions. It is therefore desirable to update the linear helicopter model continuously during the flight. In this thesis, two different recursive estimation methods are presented, LMS (Least Mean Square) and adaptation with a Kalman filter. The main purpose of the system estimation is to get a model which can be used for feedback control. In this report, the estimated model will be used to create a LQ controller with the task of keeping the output signal as close to the reference signal as possible.Simulations in this report show that adaptive feedback control can be used to control a helicopter's angular velocities and that the possibility to use an adaptive control algorithm in a real future helicopter is good.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-17637 |
| Date | January 2009 |
| Creators | Jägerback, Peter |
| Publisher | Linköpings universitet, Tekniska högskolan, Linköpings universitet, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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