Angular Rate Sensing with GyroWheel Using Genetic Algorithm Optimized Neural Networks

GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular rates. In this paper, the problem of angular rate sensing with the GyroWheel is investigated. Firstly, a simplified rate sensing equation is introduced, and the error characteristics of the method are analyzed. According to the analysis results, a rate sensing principle based on torque balance theory is developed, and a practical way to estimate the angular rates within the whole operating range of GyroWheel is provided by using explicit genetic algorithm optimized neural networks. The angular rates can be determined by the measurable values of the GyroWheel (including tilt angles, spin rate and torque coil currents), the weights and the biases of the neural networks. Finally, the simulation results are presented to illustrate the effectiveness of the proposed angular rate sensing method with GyroWheel.

[1]  Francesco Prudenzano,et al.  A neural network model of erbium-doped photonic crystal fibre amplifiers , 2009 .

[2]  Luigi Fortuna,et al.  Comparison of Soft-Sensor Design Methods for Industrial Plants Using Small Data Sets , 2009, IEEE Transactions on Instrumentation and Measurement.

[3]  Liu Gang.  Design of a Magnetically Suspended Gyrowheel and Analysis of Key Technologies , 2011 .

[4]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[5]  Hiram Calvo,et al.  A novel recurrent neural network soft sensor via a differential evolution training algorithm for the tire contact patch , 2017, Neurocomputing.

[6]  John Cameron Ower.  Analysis and control system design of an innovative tuned-rotor instrument , 2000 .

[7]  T.,et al.  Training Feedforward Networks with the Marquardt Algorithm , 2004 .

[8]  Mohammad Bagher Menhaj,et al.  Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.

[9]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[10]  Miguel Torres,et al.  Temperature Cycling on Simulated Annealing for Neural Network Learning , 2007, MICAI.

[11]  Sergio E. Ledesma-Orozco,et al.  Analysis of a variable speed vapor compression system using artificial neural networks , 2013, Expert Syst. Appl..

[12]  Steve Schultz,et al.  Demonstration of Technologies for Autonomous Micro-Satellite Assembly , 2009 .

[13]  Amir Hossein Gandomi,et al.  Assessment of artificial neural network and genetic programming as predictive tools , 2015, Adv. Eng. Softw..

[14]  Mustafa Demetgul,et al.  Fault diagnosis of rolling bearings using a genetic algorithm optimized neural network , 2014 .

[15]  Baolin Wu.  Spacecraft Attitude Control with Input Quantization , 2016 .

[16]  Jean-Didier Gayrard,et al.  Flexible Satellites: A New Challenge for the Communication Satellite Industry , 2007 .

[17]  Jeffrey Stuart Cain.  Investigation of the crossed flexure pivot and the dynamics of the momentum management system spacecraft control component and the dynamically tuned gyroscope , 1999 .

[18]  Sun Zhiyi,et al.  Application of combined neural networks in nonlinear function approximation , 2000, Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393).

[19]  Giancarlo Rufino,et al.  Multi-Aperture CMOS Sun Sensor for Microsatellite Attitude Determination , 2009, Sensors.

[20]  Jeff Cain,et al.  GyroWheel™ - An Innovative New Actuator/Sensor for 3-axis Spacecraft Attitude Control , 1999 .

[21]  David Titterton,et al.  Gyroscope technology 1 , 2004 .

[22]  Bangcheng Han,et al.  Attitude Sensing and Dynamic Decoupling Based on Active Magnetic Bearing of MSDGCMG , 2012, IEEE Transactions on Instrumentation and Measurement.

[23]  Hui Zhao,et al.  A New Multi-position Calibration Method for the Gyrowheel Using Multiple Objective Particle Swarm Optimization Algorithm , 2017 .

[24]  Li Fu,et al.  A novel calibration procedure for dynamically tuned gyroscope designed by D-optimal approach , 2013 .

[25]  Hui Zhao,et al.  Modeling and Analysis of Micro-Spacecraft Attitude Sensing with Gyrowheel , 2016, Sensors.