Modeling And Control Of A Maneuvering Reentry Warhead

With the continuous development of ballistic missile defense system, the penetra-tion problem of the ballistic missile faces increasingly severe challenge. The technique ofmaneuvering reentry warhead (MRW) with variable trajectory is one of the most impor-tant approaches to improve the penetration ability of the ballistic missile. MRW typicallyhas a more sophisticated reentry trajectory than crewed vehicles like as the Space Shut-tle or proposed crew return vehicle such as the X-38. Moreover, the missions of MRWrequire a steeper reentry ?ight path angle, followed by a pull-out into level ?ight. TheMRW must transit the entire atmosphere and robustly perform the maneuvers requiredfor the mission. The aerodynamic characteristics and environment parameters vary in alarge range and the system states vary fast during the reentry. Applying nonlinear controltheory to the control of MRW is a challenging subject for the control systems designers.Therefor, this thesis researches the control problem of variable trajectory of the MRW,and design the controller utilizing the nonlinear control theory. Based on the controllerdesign, the design and tracking of reentry maneuvering trajectory are studied. The mainresearch achievements of the thesis are summarized as follows.The six-dof nonlinear model of biconic MRW with ?aps is obtained, and the opti-mal maneuver reentry trajectory is designed via a new optimal control method—GaussPseudospectral Method. Firstly the full aerodynamic data are created using the softwarecalled U.S. Air Force Missile Datcom. Considering the typical reentry trajectory of themaneuvering warhead, the full aerodynamic force and torque model is built with the ?ightheight varying between 0km and 45km and the ?ight mach number varying between 1.5and 12. Then a multi-phases optimization strategy is proposed to deal with the difficultiesin the optimization of long-range trajectory with multiple path,state constraints. Theprecision and efficiency of the proposed method are evaluated by numerical simulation.The nonlinear model of MRW and the optimized trajectory generated re?ect the charac-teristic of reentry, and provide a suitable simulation platform for the research of controltechnique of MRW.The adaptive nonlinear dynamic inversion control method suitable for MRW is pro-posed to overcome the effect on the controller performance because of imprecise model of MRW during the reentry maneuver. The online neural network compensator is designedto cancel the effect of the model error. The simulation results show that the proposedcontrol method achieved satisfied robustness performance in the presence of large aero-dynamic uncertainties.The trajectory linearization control (TLC) method suitable for MRW is proposed toovercome the shortcoming of the linear time invariant controller in the dynamic inversioncontroller for MRW. TLC method is a nonlinear control design tool proposed recently,which combines a nonlinear dynamic inversion controller and a linear time-varying (LTV)feedback stabilizator. TLC control system achieves exponential stability along the nom-inal trajectory, therefor it provides robust stability and performance along the trajectorywithout interpolation of controller gains. The simulation results show that the TLC con-troller achieves better robust performance compared with the basic dynamic inversioncontroller of in the presence large parameter uncertainties during the reentry process.An adaptive trajectory linearization controller (ATLC) method suitable for MRW isproposed to improve the robust performance of TLC controller for MRW. Firstly for akind of multi-input/multi-output aerospace vehicle system with nonlinear model uncer-tainty, assuming the disturbances and uncertainties of the system satisfy the matchingconditions, the compound disturbances are compensated using the general dynamic fuzzyneural networks (GD-FNN). The weighting matrix of GD-FNN can be updated online.Based on the Lyapunov stability theory, the outputs of GD-FNN are proved to be boundedand the stability of the closed loop with ATLC controller is also discussed. Then theMRW controller is designed using the ATLC method. The proposed controller is verifiedby numerical simulation based on the six-dof nonlinear MRW model, which shows thatthe ATLC controller achieves better robust performance compared with the standard TLCcontroller in the presence of large parameter uncertainties during the reentry process. Thetracking results of optimal reentry trajectory show that the ATLC controller achieves thebest performance compared with the TLC conroller and the adaptive nonlinear dynamicinversion controller.