Design Of Aircraft Overload Autopilot Based On Nonlinear Model Predictive Control

With the continuous development of attack and defense countermeasure technology in air combat,the performance of existing air-to-air missiles cannot meet more and more technical and tactical requirements,it is necessary to design air-to-air missiles with higher performance,and the air-to-air missile autopilot is one of the key subsystems related to the success or failure of missile flight.The mission of the overload autopilot is to accurately control the missile according to the overload commands and then to guarantee the interception of the target.The air-to-air missile model is nonlinear and time-varying,subject to various disturbances and constraints of control parameters.With the above problems taken into account,it is of great significance to build an accurate model of air-to-air missile and design an overload autopilot with high control accuracy and strong robustness.In this thesis,dynamics modeling and design of advanced overload autopilots are carried out for air-to-air missiles.The research consists of the following:1.The precise mathematical model of an air-to-air missile is established.Based on the working principle of the missile,forces and moments acting on the missile body are analyzed,dynamic equations and kinematic equations of the missile is established.This lays the foundation for the controller design and simulation.2.The design of air-to-air missile overload autopilot is developed.Aiming at the characteristics of air-to-air missile with strong nonlinearity,various constraints and external disturbances,a design method of overload autopilot is proposed by combining generalized extended state observer with model predictive control.The generalized extended state observer is used to observe and compensate for external disturbances and model uncertainties.The model predictive control is designed based on the compensated model,which can optimize the integrated control performance of the system with all the constraints and limitations satisfied.The simulation results show that compared with the traditional two-loop overload autopilot based on PI correction,the proposed overload autopilot based on generalized extended state observer and model predictive control can greatly improve the overload control performance of missiles.3.The optimal design of overload autopilot is carried out.Aiming at the problem of large computation and poor real-time performance of the model predictive control algorithm,the optimization design is carried out in several aspects.First,function predictive control is adopted instead of model predictive control to change optimization variables from control sequence to the weights of basis functions to reduce the number of optimization variables.Then,two fast solving algorithms,the barrier interior-point method and the simplified dual neural network model,are introduced to solve the problem of long computation time in traditional quadratic programming.The simulation results show that the two improved schemes can improve the real-time performance and reduce the average computation time while ensuring the control performance.Among them,the improved barrier interior-point method has more obvious advantages in computation time consumption and is more suitable for missile control systems.