A Real-Time Adaptive High-Gain EKF, Applied to a Quadcopter Inertial Navigation System

The authors demonstrate the practical application of the adaptive high-gain extended Kalman filter (EKF) (AEKF) onboard a quadcopter unmanned aerial vehicle (UAV). The AEKF presents several advantages in state estimation, as it combines good filtering properties with an increased sensitivity to large perturbations. It does this by varying the high-gain parameter according to a metric called innovation. Unlike many adaptive observers, the AEKF is mathematically proven to globally converge, a significant advantage over the traditional EKF when considering robust controls. The AEKF is implemented on the UAV's inertial navigation system (INS). Full INSs can have problems when sensors are noisy and limited, particularly in the case of highly dynamically unstable systems such as a quadcopter. Simulation and experimental data show that the AEKF is suitable for this INS.

[1]  Nicolas Boizot,et al.  Adaptive-gain extended Kalman filter: Extension to the continuous-discrete case , 2009, 2009 European Control Conference (ECC).

[2]  A. Tornambè.  High-gain observers for non-linear systems , 1992 .

[3]  James Diebel,et al.  Representing Attitude : Euler Angles , Unit Quaternions , and Rotation Vectors , 2006 .

[4]  Holger Voos,et al.  Nonlinear tracking and landing controller for quadrotor aerial robots , 2010, 2010 IEEE International Conference on Control Applications.

[5]  J. Gauthier,et al.  Exponentially converging observers for distillation columns and internal stability of the dynamic output feedback , 1992 .

[6]  Abdelaziz Benallegue,et al.  Dynamic feedback controller of Euler angles and wind parameters estimation for a quadrotor unmanned aerial vehicle , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[7]  Holger Voos,et al.  Nonlinear control of a quadrotor micro-UAV using feedback-linearization , 2009, 2009 IEEE International Conference on Mechatronics.

[8]  P. Castillo,et al.  Stabilization of a mini rotorcraft with four rotors , 2005, IEEE Control Systems.

[9]  Young Soo Suh,et al.  Attitude Estimation by Multiple-Mode Kalman Filters , 2006, IEEE Transactions on Industrial Electronics.

[10]  Eric Busvelle,et al.  An adaptive high-gain observer for wastewater treatment systems , 2011 .

[11]  J. Gauthier,et al.  Deterministic Observation Theory and Applications , 2001 .

[12]  G. L. Santosuosso,et al.  Adaptive Observer and Kalman Filtering , 2008 .

[13]  Yuanqing Xia,et al.  Attitude Tracking of Rigid Spacecraft With Bounded Disturbances , 2011, IEEE Transactions on Industrial Electronics.

[14]  Jaechan Lim,et al.  Cost Reference Particle Filtering Approach to High-Bandwidth Tilt Estimation , 2010, IEEE Transactions on Industrial Electronics.

[15]  Jean Picard.  Efficiency of the extended Kalman filter for nonlinear systems with small noise , 1991 .

[16]  F. Allgower,et al.  An adaptive high-gain observer for nonlinear systems , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[17]  H. Khalil,et al.  Output feedback stabilization of fully linearizable systems , 1992 .

[18]  Philippe Martin,et al.  The role of propeller aerodynamics in the model of a quadrotor UAV , 2009, 2009 European Control Conference (ECC).

[19]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[20]  Taeyoung Lee,et al.  Geometric tracking control of a quadrotor UAV on SE(3) , 2010, 49th IEEE Conference on Decision and Control (CDC).

[21]  Yisheng Zhong,et al.  Robust Attitude Regulation of a 3-DOF Helicopter Benchmark: Theory and Experiments , 2011, IEEE Transactions on Industrial Electronics.

[22]  J. Gauthier,et al.  A simple observer for nonlinear systems applications to bioreactors , 1992 .

[23]  Jonathan P. How,et al.  Comparison of Fixed and Variable Pitch Actuators for Agile Quadrotors , 2011 .

[24]  Felipe Espinosa,et al.  UAV Attitude Estimation Using Unscented Kalman Filter and TRIAD , 2012, IEEE Transactions on Industrial Electronics.

[25]  P. Krishnaprasad,et al.  Dynamic observers as asymptotic limits of recursive filters , 1982, CDC 1982.

[26]  Nicolas Boizot,et al.  Using an Adaptive High-Gain Extended Kalman Filter With a Car Efficiency Model , 2010 .

[27]  Seth B. Anderson,et al.  Historical Overview of V/STOL Aircraft Technology , 1997 .

[28]  Sauro Longhi,et al.  A Model-Based Fault Diagnosis System for a Mini-Quadrotor , 2009 .

[29]  Suzanne Lesecq,et al.  Quadrotor attitude estimation with data losses , 2009, 2009 European Control Conference (ECC).

[30]  Vinay A. Bavdekar,et al.  Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter , 2011 .

[31]  Robert Mahony,et al.  Modelling and control of a large quadrotor robot , 2010 .