Air-to-Air Missile Intelligent Guiding And Control Based On Target Intention

Air-to-air missile has become the main sky battle weapon due to its precise guidance and powerful weapons, and it has been widely studied in all over the world. With the continuous progress of military science, we must accurately identify the enemy target combat intention firstly due to the rapid development of air threat and diversification of aerial target, if one wants to grasp the priority of the battlefield. Then, the missile guidance law can be chosen based on the target intention to increase the attacking accuracy and combat efficiency. This dissertation studies air-to-air missile intelligent guidance and control technology based on target intention. The main works are as follows:Firstly, a nonlinear flight motion mathematical model of the air-to-air missile is established. System of coordinates and the transfer of axes are introduced to analyze the force and the moment. Based on this, the dynamic equation and the kinematics equation are given. And the six degrees of freedom twelve equations of flight motion are derived. For the convenience of further research about control law of missile, combining the singular perturbation theory and the time scale separation principle, the dynamics of missile is divided into two loops, fast loop and slow loop.Then, the intelligent terminal guidance law is studied for air-to-air missile. The three-dimensional predictive control guidance(PCG) law is studied based on sliding mode disturbance observer for air-to-air missile with parameter uncertainties and external disturbances and highly maneuvering target. The sliding mode disturbance observer is applied to approximate the compounded disturbance. The guidance law of air-to-air missile is designed by nonlinear predictive control method based on parallel approach principle. The stability of closed-loop system is analyzed using Lyapunov method. Simulation results illustrate that the developed PCG law is better than proportional navigation(PN) in performance.Following, the problem of target intention prediction is studied by the adaptive neural-fuzzy inference system(ANFIS).The target intention prediction classification model is established by using the ANFIS method to realize the classification of target intention prediction information. The sample training data of influencing target intention are obtained by the characters of position angle, horizontal speed, course angle, distance and height. The fuzzy inference system is obtained by training above data. The ANFIS process parameters and conclusion parameters are predicted and optimized by the error back propagation algorithm. The target intention prediction result is not obtained until the value of error function meets the required precision or the number of circulation achieves the total number of iterations. With an example simulation, the simulation results show that it is better than probabilistic neural network(PNN) in the intention prediction result.Finally, the missile guidance law is chosen based on the air target intention and the control law is studied for air-to-air missile. The advantages and disadvantages of several common guidance laws are analyzed. The air targets are divided into a type of non attack and attack targets based on the classification results of aerial target intention. And, the missile guidance law is thus selected. The result is verified using Matlab graphical user interface. Simulation results illustrate that the chosen missile guidance law can follow the trajectory of targets well and ensure the overall operational performance and firing accuracy. A sliding mode control method based on sliding mode disturbance observer is proposed to solve the influence with the disturbance of missile attitude angles layer and aerodynamic parameter uncertainty. The attitude control is designed respectively for slow loop and fast loop of air-to-air missile. The sliding mode disturbance observer(SMDO) is employed to approximate the external disturbance of fast loop. Based on this, the sliding mode control law of fast loop is designed. Adaptive dynamic sliding mode control is designed in the slow loop which only considering the influence of system uncertainty. The stability of closed-loop system is analyzed using Lyapunov method. Simulation results show that satisfactory attitude control performance is achieved.