Research On Attitude Determination And Control Of Small Satellite Based On Nonlinear Filter

With fast development of space technology, modern small satellite plays a more and more important role due to its advantages of high performance, low-risk, short periods and low-cost. However, sensors with low precision and power consumption are usually adopted for small satellite because of the limitations on cost, size, mass and power, which decreses the level of attitude determination and control system (ADCS) and the whole performance. To solve this problem, methods for high precision attitude determination and control with low precision sensors are presented in this dissertation.The key technologies presented here are listed as following:Several EKF based attitude determination methods are studied. Comprehensive research on traditional EKF is carried out, and an observation equation is derived from observation vectors, which can enrich the traditional observation equation and enhance the utilization efficiency of observation data. Then the flow of attitude determination is designed and several improved EKF algorithms are proposed, all of which can achieve better accuracy.The application of Federal Filter and Predictive Filter on snall satellite attitude determination is investigated. To enhance the accuracy and reliability of information distribution gene in Federated Filter, a new method of information distribution gene is proposed based on better utilization of new observation information; so as to further improve the attitude determination precision. To improve the mode accuracy and the convergence efficiency of angle velocity in Predictive Filter, a new approach to estimate the mode error and angle velocity error concurrently by decoupling is proposed, which can better handle nonlinear and non-Gaussian white noises. The high performance of filter precision of these two new proposed methods are verified by simulation results.The accelerating Particle Filter method and its application in small satellite attitude determination are discussed. The idea of limit approximation is introduced into to the Particle Filter theory, which proves the feasibility of estimating state variables with fewer amounts of particles. To enhance the accelerating Particle Filter method, a new mix-resampling method is put forward by introducing"local-design"into the theory of Bayes Filter and Sequential Importance Sampling, based on which extension Particle Filter to estimate unknown parameters is further studied. At last, a general flow of parameter estimation by accelerating Particle Filter is developed, and tested in the example of small satellite attitude determination, which verifies its high performance of filter precision and even better compared with the aforementioned approaches.The small satellite attitude control based on sliding mode control is studied. The I/O linearization based adaptive fuzzy sliding mode control is firstly investigated, which achieves good control performance. Based on this method, a non-singular terminal adaptive fuzzy sliding mode control approach is proposed, and its capability of fast convergence in attitude control within limited time is proved. To perfect this research, a new control policy of global fast integral terminal sliding mode control is put forward, which can better improve fast convergence speed and anti-jamming effect. The three foregoing control policies are combined with accelerating Particle Filter and tested by simulations, which have verified their reliability and validity.The nonlinear filter method and variable structure control theory proposed in this dissertation have the powerful capacities to deal with nonlinearity and benefit to implement high-precision attitude determination and control with low-precision sensors in order to improve the system performance for small satellite. The results in this dissertation can provide reference and technique support for future research in this field.