Reasearch On Flight Control System Of Aircraft Based On Improve PSO-PID Algorithm

The four-axis aircraft is powered by four propellers to achieve different flying motions.Unlike a common helicopter,its flight does not require a tail rotor to balance the torque force.A series of movements such as pitching,rolling,yaw,take-off and landing can be achieved only by adding and slowing down four propellers.In order to improve the flight stability and accuracy of aircraft,more precise mathematical models and control algorithms have been put forward.The control effect of the traditional simple PID controller depends on the selection of three parameters,and there is no scientific theoretical basis for the setting process.It is impossible for the modern industry and service industry to meet the requirements of the high precision and high efficiency of the aircraft control.Because particle swarm optimization(PSO)is simple and efficient,it is often used in the tuning of three parameters of PID controller.The tuning effect of PID parameters is optimized by using the algorithm's wide range optimization characteristics.But in the later stage of iteration,the step size of particle update is smaller and smaller,and it is easy to fall into local optimum,which leads to premature convergence of the algorithm,that is,"premature".Based on this article,an improved method is proposed.By introducing the concept of social learning in particle swarm optimization(PSO),the particle does not learn from the global optimal value and the individual historical optimal value,but to the random particle learning which is better than itself.In order to eliminate the influence of improper adjustment of the previous iteration on this iteration,dynamic inertia weight is introduced to improve it.This improved algorithm will significantly improve the control efficiency and control accuracy.In this paper,the dynamic equation and mathematical model of the four axis aircraft are analyzed in depth,and the improved social learning particle swarm optimization(PSO)algorithm is introduced to adjust the parameters of the PID controller.Finally,the results of Matlab/Simulink simulation and flight experiment are verified to verify the control effect.The specific contents are as follows:1.the development history,research background,application prospects and research significance of the four axis aircraft are introduced in detail.2.according to the law of Newtonian mechanics,the modeling process of the aircraft is deeply analyzed,and the whole control process is divided into two parts: position PID control and attitude PID control.3.the common controller and the common intelligent parameter tuning algorithms are analyzed and introduced respectively,and their advantages and disadvantages are compared and demonstrated,and the specific reasons for the final selection of particle swarm optimization to adjust the PID parameters are explained.4.the principles and implementation of PSO algorithm,PID controller and PSO-PID algorithm are introduced in detail.On this basis,two improved algorithms are proposed,namely adaptive PSO-PID algorithm and improved social learning PSO-PID algorithm.The two algorithms are described in detail,and the advantages and disadvantages of the two algorithms are compared according to simulation and flight experiments.The improved social learning PSO-PID algorithm is much better than the standard PSO-PID control algorithm and the adaptive PSO-PID control algorithm in the control effect.5.Matlab/Simulink simulation experiment is carried out through the mathematical model established before.The simulation results are compared and analyzed.Finally,the flight test is carried out in the aircraft.The results also prove the effectiveness and superiority of the control method.