Robust Gust Rejection on a Micro-air Vehicle Using Bio-inspired Sensing

Growing demand for robust, low-computation sensing and control of micro-air vehicles motivates development of new technology. A MEMS wind flow sensor was previously developed at the University of Maryland, drawing inspiration from setae structures seen in biology. In this work this sensor is integrated onto a quadrotor platform and utilized for sensing a gust perturbation. Suitable signal processing methods were used to isolate the gust-related perturbation from other ambient fluctuations affecting the sensor. The problem of gust rejection is then formulated using standard tools from robust control theory and a controller is obtained using μ–synthesis. Theoretical analysis of the μ controller’s performance improvement is carried out with simulations. A robustly stable controller was implemented on a quadrotor micro-air vehicle to improve lateral state regulation in the presence of a lateral gust stream. Flight testing revealed attenuation of the lateral velocity and perturbation from the projected path.

[1]  Robert C. Nelson,et al.  Flight Stability and Automatic Control , 1989 .

[2]  Ella M. Atkins,et al.  An Empirical Model of Rotorcrafy UAV Downwash for Disturbance Localization and Avoidance , 2015 .

[3]  J. Sean Humbert,et al.  Experimental Study of Gust Effects on Micro Air Vehicles , 2010 .

[4]  Frank L. Lewis,et al.  H-Infinity Static Output-feedback Control for Rotorcraft , 2006, J. Intell. Robotic Syst..

[5]  James Sean Humbert,et al.  Bio-inspired wind frame state sensing and estimation for MAV applications , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  J. Engel,et al.  Development and characterization of an artificial hair cell based on polyurethane elastomer and force sensitive resistors , 2005, IEEE Sensors, 2005..

[7]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .

[8]  A. Reynolds,et al.  A single wind-mediated mechanism explains high-altitude ‘non-goal oriented’ headings and layering of nocturnally migrating insects , 2010, Proceedings of the Royal Society B: Biological Sciences.

[9]  Eugene A. Morelli,et al.  Aircraft system identification : theory and practice , 2006 .

[10]  Gregg Abate,et al.  Flight Controls and Performance Challenges for MAVs in Complex Environments , 2008 .

[11]  B. Ross Barmish,et al.  Robustness of Luenberger Observers: Linear Systems Stabilized via Nonlinear Control , 1984 .

[12]  Nabil Aouf,et al.  H2 and H-optimal gust load alleviation for a flexible aircraft , 2000 .

[13]  Marcel Dijkstra,et al.  MEMS based hair flow-sensors as model systems for acoustic perception studies , 2006, Nanotechnology.

[14]  Nabil Aouf,et al.  H/sub 2/ and H/sub /spl infin//-optimal gust load alleviation for a flexible aircraft , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[15]  Jishnu Keshavan,et al.  MAV stability augmentation using weighted outputs from distributed hair sensor arrays , 2010, Proceedings of the 2010 American Control Conference.

[16]  Derek A. Paley,et al.  Dynamic control of autonomous quadrotor flight in an estimated wind field , 2013, 52nd IEEE Conference on Decision and Control.

[17]  N. Chen,et al.  A monolithic integrated array of out-of-plane hot-wire flow sensors and demonstration of boundary-layer flow imaging , 2005, 18th IEEE International Conference on Micro Electro Mechanical Systems, 2005. MEMS 2005..

[18]  Steven L. Waslander,et al.  Wind Disturbance Estimation and Rejection for Quadrotor Position Control , 2009 .