Trajectory Optimization And Tracking Control Technology For Reusable Launch Vehicle

Since the kinematic and kinetic characters of Reusable Launch Vehicles(RLVs)include strongnonlinearity and strong coupling,effective nonlinear optimal controllers are helpful to accomplish flight missions and reduce control energy.However,many factors make it difficult to design such controllers.Firstly,unlike vehicles with subsonic and supersonic velocities,the flight characteristics of RLVs are based on hypersonic velocity,which cannot be learned through wind tunnel test.Thus,aerodynamic coefficients of RLVs are very uncertain.Secondly,flight missions of RLVs covers huge altitude variation,dramatic change in atmospheric environment leads to marked variation in RLV's kinematic and kinetic characters as well as model parameters.Lastly,during flight missions,the atmospheric environment cannot be entirely predicted,which means that RLVs may suffer strong external disturbances.In conclusion,controllers should have high robust performance to guarantee the completion of flight missions.This thesis researches RLV reentry optimal trajectories and tracking controllers in terms of trajectory following.Based on an RLV's 12-state kinematic and kinetic model,several tracking controllers have been designed considering uncertain model,external disturbances as well as initial trajectory error.The following is a brief overview of this thesis.Firstly,atmosphere model and the RLV's model including 6-state guidance model for reentry trajectory optimization as well as 12-state kinematic and kinetic model for trajectory tracking control are introduced.Then,differential evolution algorithm and pseudospectral method are used to design global optimal RLV reentry trajectory collaboratively.Pseudospectral method which is based on the Pontryagin's minimum principle can be used to obtain local optimal solution quickly.Differential evolution algorithm generates initial guess values for pseudospectral method randomly,by setting proper fitness function,global optimal solution and less terminal trajectory error can be obtained through variation,crossover and selection.Simulation result demonstrates the effectiveness of collaborative optimal scheme.Thirdly,based on the RLV's 12-state nominal kinematic and kinetic model,a set of optimal trajectories was planned according to initial and terminal constraints during one phase of RLV reentry mission,and the optimal index is the minimum control energy.As for the model taking initial trajectory error,uncertain model and external compound disturbances into account,sliding mode techniques including high-order sliding mode disturbance observer(HOSMDO),super twisting finite time sliding mode control and sliding mode feedback control are used to design robust controller which made the flight path and attitude angles convergent to the nominal trajectories.System convergence has been proved by the Lyapunov method.Simulation result shows the robustness and convergence of the control scheme.Then,based on the nominal attitude angle trajectory and model with uncertain aerodynamic coefficients,the attitude angel error dynamic is derived.An H-infinity control scheme is designed according to the error dynamic.A stable manifold method is used to obtain the analytical approximate solution of Hamilton-Jacobi-Inequality(HJI),which is utilized to generate the feedback law in order to regulate the error to zero.This scheme generated a set of reference attitude angular rate signal.HOSMDOs and super twisting sliding mode control laws are used to make attitude angular rate track the reference signal.System convergence has been proved by Lyapunov method.Simulation result shows the robustness and convergence of the control scheme.Finally,based on the nominal RLV optimal trajectory,the 6-state kinematic model were linearized,and a linear time varying(LTV)system in regard to error was established.An off-line model predictive method is used to design a regulation control law for the LTV system in order to regulate the error to zero at an exponential damping rate.This regulation law was applied in the original nonlinear system,then the model uncertainty and external compound disturbances can be rejected.System stability has been proved by the Lyapunov method.Simulation result shows the convergence of flight path error and robustness of this control scheme.