Design And Implementation Of Fuzzy Control Algorithm For Air Robot Application

In recent years,robot technology has developed very rapidly,especially air robots,its low price has attracted people’s attention.In many aspects of production and life,air robots have great practical value.Therefore,many countries and scholars are committed to the study of air robots,although made a lot of research results,but there are still many problems that can not be solved,especially in the field of control needs more in-depth study.The traditional PID controller is very effective for the control of the controlled object which can establish the precise mathematical model.It has the advantages of simple algorithm,good robustness and high reliability,but for those with nonlinear and time-varying uncertainties,Control the object,the application of traditional PID controller is difficult to achieve effective control.In order to further improve the control accuracy of the system,this is based on the traditional PID controller,can solve the control problem of the controlled object with nonlinear and time-varying uncertainties by combining the optimized fuzzy controller.The optimization algorithm is based on the control rules obtained by the large data training of different environments under the line,and the control rules are used for effective control,The advantage is that Precise mathematical model of control object.classical PID control and fuzzy PID control as a control algorithm comparison.The simulation model of the system of the aircraft is built by MATLAB/Simulink,the PID controller and the fuzzy PID controller are designed and the simulation test of the algorithm is carried out.The experimental results show that the rise time of the system is 0.75s,the adjustment time is 0.6s,the overshoot is 0.04,the steady state error is 0.8%,which can meet the control requirements of the air robot.The improved control algorithm satisfies the design requirements and indexes in function and performance,and the control algorithm has the advantages of strong environment adaptability,high robustness and high control precision.