|M.Sc Student||Shahar Michael Simantov|
|Subject||Stabilization and Control of a Miniature Remotely Piloted|
Flight Vehicle for Hovering and Omni-Directional
|Department||Department of Aerospace Engineering||Supervisor||Professor Grunwald Arthur|
A reliable vehicle state estimation is presented used in controlling an indoor unmanned miniature vehicle. The method enables keeping the vehicle level, as well as tracking translatory velocity commands in the horizontal and the vertical direction, and tracking a yaw rate command, determined by the operator. The control system is based on estimation of the vectors of translational and angular motion and estimation of the roll and pitch attitude angles.
The estimation process uses an Extended Kalman Filter, which utilizes the optical information derived from the optical flow field of miniature vehicle-mounted TV cameras and low-cost inertial sensors. Unbiased bounded estimates of the roll and pitch angles are obtained, with an estimation accuracy that is satisfactory for stabilizing and controlling of the aircraft.
The method was validated by means of numerical simulations and partial laboratory experiments. The simulation results clearly indicate that the idea of estimating motion parameters by combining optical flow field measurements and inertial measurements is valid.
The experimental evaluation dealt with the motion parameter estimation of a payload mounted on a three-axis servo-controlled high-precision flight table. The roll and pitch angles were estimated. The motion was limited to angular motion only, in three degrees of freedom. The estimation results obtained from the experiment indicate that under the conditions of the experiment, the roll and pitch angles can be estimated with accuracy of 0.5 degrees.
The results of the numerical simulations and of the experimental evaluation clearly indicate that the suggested method yields bounded estimation errors with sufficiently accurate roll and pitch angle estimates that enable stabilization and control of the miniature aircraft.