Research On Unmanned Helicopter Control Technology Based On Particle Swarm Optimization

As a kind of rotorcraft,unmanned helicopter has the flying ability of fixed-point hovering,vertical take-off and landing and multi-direction flight,which has the advantages of convenient deployment,flexibility and wide application,and plays an increasingly important role in both military and civil modernization.This paper mainly focuses on the establishment of mathematical model of unmanned helicopter,improvement of particle swarm optimization algorithm,controller design and simulation.Firstly,this paper takes the small unmanned helicopter as the research object.The ground coordinate system and body coordinate system are established,and the transformation of coordinate system is deduced.The nonlinear mathematical model is obtained by analyzing the force and moment of each part of the helicopter fuselage and its kinematics equation and six degrees of freedom dynamic equation.Then the linearization model is obtained by using the small perturbation method.Secondly,the improved particle swarm optimization algorithm is proposed.Based on the analysis of the parameters,the basic particle swarm optimization algorithm is considered to be prone to fall into local minimum and poor convergence performance.A method combining adaptive weighting and transforming learning factors is adopted.Through two classical test functions Ackley function and Schaffer function verification,the results show that the method has good convergence speed and searching precision.The explicit model tracking control system is used to solve the problem of strong coupling between the channels of unmanned helicopter.According to the requirement of operation quality,four independent channels of pitch,roll,course and total distance are designed,and then the control array is designed.Because the forward gain diagonal array and integral constant array in the control array are usually timeconsuming and laborious,the improved particle swarm optimization algorithm is adopted to deal with them to reduce the workload and improve the work efficiency.Introduce the linear quadratic regulator on that basis of the explicit model,the weight matrix Q and R of the design state feedback control are also use to process the linear quadratic weight matrix Q and R to improve the controller performance.Finally,It is prove by simulation that that modified particle swarm algorithm can optimize the design of the control,which improves the design efficiency compared to the traditional design scheme,which also guarantees the performance requirement of the system.The unmanned helicopter flight control platform for the overall design,studied the information system work process,on the flight control system composition and its function implementation were studied.On the basis of the summary of the paper,the existing problems and the next step of the research are put forward to make preparations for the future work.