In-Flight Estimation of Center of Gravity Position Using All-Accelerometers

Changing the position of the Center of Gravity (CoG) for an aerial vehicle is a challenging part in navigation, and control of such vehicles. In this paper, an all-accelerometers-based inertial measurement unit is presented, with a proposed method for on-line estimation of the position of the CoG. The accelerometers' readings are used to find and correct the vehicle's angular velocity and acceleration using an Extended Kalman Filter. Next, the accelerometers' readings along with the estimated angular velocity and acceleration are used in an identification scheme to estimate the position of the CoG and the vehicle's linear acceleration. The estimated position of the CoG and motion measurements can then be used to update the control rules to achieve better trim conditions for the air vehicle.

[1]  Pei-Chun Lin,et al.  Design and Implementation of a Nine-Axis Inertial Measurement Unit , 2012, IEEE/ASME Transactions on Mechatronics.

[2]  Sungsu Park,et al.  Design of accelerometer-based inertial navigation systems , 2005, IEEE Transactions on Instrumentation and Measurement.

[3]  Yiannos Manoli,et al.  Design, geometry evaluation, and calibration of a gyroscope-free inertial measurement unit , 2010 .

[4]  Paul Zarchan,et al.  Fundamentals of Kalman Filtering: A Practical Approach , 2001 .

[5]  Zhou Jun,et al.  Spacecraft center of mass online estimation based on multi-accelerometers , 2010, 2010 2nd IEEE International Conference on Information Management and Engineering.

[6]  Paulo S. R. Diniz,et al.  Adaptive Filtering: Algorithms and Practical Implementation , 1997 .

[7]  Pei-Chun Lin,et al.  Design and implementation of a 12-axis accelerometer suite , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Jing Zhang,et al.  Modeling and attitude control of aircraft with center of gravity variations , 2009, 2009 IEEE Aerospace conference.

[9]  Jing Zhang,et al.  Modeling and attitude control of aircraft with variations in mass and center of gravity , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[10]  D. Simon Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[11]  Mark Costello,et al.  In-Flight Estimation of Helicopter Gross Weight and Mass Center Location , 2009 .

[12]  M. T. Tham,et al.  Covariance resetting in recursive least squares estimation , 1988 .

[13]  Rafael Fierro,et al.  Adaptive Control of a Quadrotor with Dynamic Changes in the Center of Gravity , 2011 .

[14]  B. Ravani,et al.  Design and Implementation of a Mechatronic, All-Accelerometer Inertial Measurement Unit , 2007, IEEE/ASME Transactions on Mechatronics.

[15]  Automated Estimation of an Aircraft ’ s Center of Gravity Using Static and Dynamic Measurements , 2008 .