| Three dof helicopter model is a nonlinear, control variables, unstable characteristics of complex system, and it is difficult to analysis to get the exact mathematical model. Particle swarm optimization neural network control algorithm is the issue of people's attention in recent years. Based on particle swarm optimization neural network the control algorithm for control strategy of the GOOGOL company research and development of three dof helicopter control problem of the model.This article main research content is as follows:1,A hardware structure of dual rotor helicopter,which has the basic characteristics of its operation method, the stress of the details about its flight characteristics and physics equation, under different condition, physical expression list show different motion state, the state variables listed movement expression of matrix expression system, build the system state equation of movement of the aircraft, and the stability of state equation, can be accused of sexual and analysis the control model.2, Firstly, introducing a genetic particle swarm optimization algorithm to optimize the weights of neural network and PID initial value, prevent the set parameters into local extremum, again is introduced, the whole order neurons with RBF neural network PID control algorithm, through the Jocabian identification information online setting value of PID, achieve the desired control objective, and matrix of the object is set to double rotor helicopter model, make MATLAB Simulink module structures, the simulation and control experiment.3, the particle swarm optimization neural network setting PID algorithm isapplied to the double rotor model for real-time flight, can guarantee the stability of the system, verify the control algorithm is feasible.4, also the results of simulation and real-time control showed the lack of control algorithm research, inductive analysis and, after looking control algorithm study follow-up work. |
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