Effect of time-varying factors on the drift model of Electrostatically Supported Gyro
Time-varying factors are extremely important in both dual-axis servo turntable and Electrostatically Supported Gyro (ESG) by affecting the testing of ESG's drift model. In this paper, we model four time-varying factors, gyro case mis-alignment angle, installation error between gyro and inner ring platform, turntable base fluctuation, and null position drift of turntable's angle sensor, as a polynomial of time in the drift model for pole ESG. Based on the kinematic formula of turntable in pole gyro mode, we derive the relationships between the time-varying factors and angles of inner and outer rings of the turntable. Then the cases that these four time-varying factors affect the trajectory of turntable are analyzed term-by-term. We find that the constant drift, gravity-related drift and random drift are greatly affected by these four factors. In the light of these analyses, several basic principles to control these factors are further proposed.
Nonorthogonality of mean platform frame for Electrostatically Supported Gyro on turntable
Case rotational auto-compensation is an effective technique to enhance the accuracy of Electrostatically Supported Gyro (ESG). However, the usage of such technique will introduce additional case rotational signal in the measured readout when ESG is tested on servo turntable. To accurately identify the constant and random drift coefficients of ESG, it is necessary to smooth the measured readout by filtering the case rotational signal. More importantly, one should check whether or not the mean platform frame is orthogonal after smoothing the readout, because nonorthogonality could introduce errors and therefore degrade the estimation precision of ESG's drift model. In this paper, we propose a framework to check the nonorthogonality of mean platform frame for electrostatically supported gyro on turntable. Specifically, we firstly formulate the mean platform frame by measured readout and analyze the orthogonality of the frame by checking if the dot product of the three axes of the frame is equal to zero. We find that nonorthogonality is mainly determined by case mis-alignment angle between the case rotational axis and momentum axis of ESG. Furthermore, we carry out some numerical study to characterize the relationship between case mis-alignment angle and the accuracy of gyro drift coefficient identification. Our simulation result shows that the magnitude of case mis-alignment angle will affect the identification accuracy of drift coefficient of ESG, which may imply the dependence between nonorthogonality and the identification accuracy.
State estimation for integrated vehicle dynamics control
This paper discusses a vehicle controller and a state estimator that was implemented and tested in a vehicle equipped with a combined braking and chassis control system to improve handling. The vehicle dynamics controller consists of a feed forward body roll compensation and a feedback stability controller. The estimator is based on a non-linear vehicle model combined with an extended Kalman filter. The Kalman filter is also connected to an algorithm, which estimates the tyre-road friction coefficient. The developed estimator was tested in a vehicle. Good results were achieved for normal and extreme driving manoeuvers.