Data-based Attitude Control Of Combined Spacecraft With Noncooperative Targets

With the continuously development of space techonology and the increasing demand for exploration of outer space,competition in outer space has gradually become a new strategic commanding height.All countries are committed to building space forces.In order to extend the service life of spacecraft,enhance the performance of spacecraft,and build a new combined spacecraft,on-orbit service technologies such as on-orbit maintenance and on-orbit refueling have also become the focus of research.In the process of space force competition between countries and on-orbit maintenance,it will inevitably encounter the need to arrest non-cooperative target spacecraft.The parameters of noncooperative target spacecraft may be unknown.After serving spacecraft catches noncooperative target spacecraft,the attitude stability control of the combined spacecraft is the primary task.Because the parameters of the combined spacecraft attitude control system are unknown,the traditional attitude control methods can no longer meet the control requirements.By data-driven control method,without relying on the exact model of the system,the controller that satisfies the requirements can be obtained with sufficient input and output data.In this paper,a non-cooperative target spacecraft attitude stabilization controller is designed based on nonlinear dynamic model and linear model respectively.In Chapter 3,the optimal controller is designed by the nonlinear optimal control theory based on the nonlinear system model of combined spacecraft with non-cooperative target.In nonlinear optimal control theory,the solution of Hamilton-Jacobi-Bellman(HJB)equation is very difficult.There is no method to get the analytical solution of HJB equation now.In addition,the parameters of the combined spacecraft attitude control system are unknown.In view of the above two problems,this chapter uses the polynomial approximation method to obtain the approximate solution of the HJB equation according to the approximate theory.At the same time,it does not need the system parameter information and solves the problem of unknown system parameters.Chapter 4 uses the adaptive dynamic programming method to design the assembly spacecraft attitude controller.Firstly,the non-cooperative target spacecraft attitude control system model is linearized near the equilibrium point,obtaining a linear state space model.In the state space model of the spacecraft attitude control system of the noncooperative target assembly,the parameter matrix is unknown partially,but the structure of the system parameter matrix is known,and the system parameter matrix of serving spacecraft is known accurately.According to this feature,the combined spacecraft attitude control system can be viewed as a combination of a known part and an unknown part,which provides convenience for the follow-up controller design.Then,the optimal controller theory is used to give the form of the optimal controller.To solve the problem of selecting the matrix Q in algebraic Riccati,the algebraic Riccati equation is replaced by the parametric Lyapunov equation.The Kleinman iterative algorithm is used to solve the algebraic Riccati equation.As for the problem that the spacecraft system parameters is unknown,the input and output datas of the system are fully used to avoid the system matrix A and B,and the iterative algorithm is used to obtain the approximate optimal linear feedback gain * and then get the approximate optimal controller *.Finally,numerical simulation experiments verify the effectiveness of the controller designed in this chapter.