Miniature aerial vehicles (MAVs) are finding applications in a number of civilian domains in which their autonomous operations are desirable. Applications of miniature aerial vehicles in different areas are growing exponentially due to technological advancement in areas such as computing, sensing, and communication, and due to advantages offered by these vehicles in terms of safe and economic operations. Due to the drive to keep cost of MAVs low, or lack of available technology and accurate sensors, exact measurement of pertinent signals and states of these kinds of nonlinear systems is not always possible. This necessitates the development of algorithmic tools such as observers that can be used to enhance the performance of sensors and measurement devices. The more complex a control system becomes, the more difficult it becomes to measure the states of the system accurately, which inherently makes the development of observers more challenging. In this paper, state observer and control system design for a small coaxial helicopter are presented. The states are observed with three different methods and compared for designing a classical pole-placement controller (based on a linearized model of the plant) and applied to a coaxial helicopter. The observer design methods used in this paper are based on Kalman filter and full- and reduced-order Luenberger observers. Numerical simulations have been carried out to illustrate the proposed techniques. Comparison of the three proposed methods confirms the intuitive notion that, in case of noisy systems, using Kalman filter method yields more accurate results as compared with the Luenberger methods.
Control of Microcoaxial Helicopter Based on a Reduced-Order Observer
Journal of Aerospace Engineering ; 29 , 3
2015-10-30
Article (Journal)
Electronic Resource
Unknown
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