Article
Turbulence Effects on Modified State Observer-Based
Adaptive Control: Black Kite Micro Aerial Vehicle
Venkatasubramani S. R. Pappu
1,
*, James E. Steck
1,†
and Guruganesh Ramamurthi
2,†
1
Department of Aerospace Engineering, Wichita State University, Wichita, KS 67260, USA;
james.steck@wichita.edu
2
CSIR–National Aerospace Laboratories, Bangalore 560017, India; rguruganesh@nal.res.in
* Correspondence: vxsubbareddiarpappu@wichita.edu; Tel.: +1-316-558-2152
† These authors contributed equally to this work.
Academic Editor: Michael Wing
Received: 1 November 2015; Accepted: 26 January 2016; Published: 5 February 2016
Abstract:
This paper presents the implementation of a modified state observer-based adaptive
dynamic inverse controller for the Black Kite micro aerial vehicle. The pitch and velocity adaptations
are computed by the modified state observer in the presence of turbulence to simulate atmospheric
conditions. This state observer uses the estimation error to generate the adaptations and, hence, is
more robust than model reference adaptive controllers which use modeling or tracking error. In
prior work, a traditional proportional-integral-derivative control law was tested in simulation for
its adaptive capability in the longitudinal dynamics of the Black Kite micro aerial vehicle. This
controller tracks the altitude and velocity commands during normal conditions, but fails in the
presence of both parameter uncertainties and system failures. The modified state observer-based
adaptations, along with the proportional-integral-derivative controller enables tracking despite these
conditions. To simulate flight of the micro aerial vehicle with turbulence, a Dryden turbulence model
is included. The turbulence levels used are based on the absolute load factor experienced by the
aircraft. The length scale was set to 2.0 meters with a turbulence intensity of 5.0 m/s that generates a
moderate turbulence. Simulation results for various flight conditions show that the modified state
observer-based adaptations were able to adapt to the uncertainties and the controller tracks the
commanded altitude and velocity. The summary of results for all of the simulated test cases and the
response plots of various states for typical flight cases are presented.
Keywords: modified state observer; adaptive control; micro aerial vehicle
1. Introduction
Micro aerial vehicles (MAV) have recently gathered much attention for use in both civil and
military applications. Research is being carried out in developing a robust and safe micro aerial
vehicles in various laboratories all over the world. Effort is also made to develop a feasible flight
certification of the vehicle.
In order to build a robust vehicle which can be flown in uncertain environments and also by
less-skilled pilots, adaptive control systems have been developed for general aviation aircraft at
Wichita State University. The work has been based on the neural network based model reference
adaptive controller (MRAC) work at NASA, by J.E. Steck and others [
1
–
3
]. The published research
work were referred to aid in the development of the flight control system for the Black Kite MAV
model. Arning et al. [
4
] shows an integrated autopilot design for DO-MAV using Micro Electro
Mechanical System (MEMS) sensors. They presented an optimized flight control law design for roll
control by varying the aircraft configuration and control parameters. Jordan et al. [
5
] described the
Aerospace 2016, 3, 6; doi:10.3390/aerospace3010006 www.mdpi.com/journal/aerospace
