Multi-dimensional Taylor Network Optimal Control Of Unmanned Helicopter Flight

With the advancement of materials and flight control technology since the 21 st century,unmanned helicopters have also made great progress.Unmanned helicopters have quickly gained attention due to their small size,convenient take-off and landing,and high agility.Take military area as example,unmanned helicopters have aerial reconnaissance and serve as target aircraft.Meanwhile,unmanned helicopters have also broadened prospects of civilian application such as forest fire prevention monitoring and high voltage power line detection.The three-degree-of-freedom helicopter model is not a simple single-input and single-output controlled object.On the contrary,it is a system with multiple inputs and multiple outputs.The system is strongly nonlinear,highly coupled and unstable,which lead the difficulties to satisfy the control performance by taking advantage of traditional control methods.Therefore,the research on unmanned helicopters has great theoretical and engineering significance and economic value.This article takes unmanned helicopter as the control object,adopts PID control in classic control method and fuzzy PID control in modern control method to design the controller.In view of the complexity and difficulty of unmanned helicopter control,proposes a multi-dimensional Taylor Network(MTN)optimal control scheme for unmanned helicopter flight,highlighting the advantages of the higher-order multi-dimensional Taylor Network optimal control in interference and other environments,and improving unmanned helicopters.Helicopter’s dynamic performance,robustness and anti-jamming performance.Compare the advantages and disadvantages of the three control methods.The main contents of this article are as follows:1.Establish the mathematical model of unmanned helicopter dynamics.In order to make the established mathematical model suitable for the actual flight conditions of unmanned helicopters,a speed limit link was added to the mathematical model.2.This thesis adopts two control modes.The first mode has three channels(elevation angle θ,roll angle ?,and heading angle ψ)plus altitude.The input and output of the second mode are three-dimensional coordinates(x,y,z)plus four channels of heading angle,which is ready for the trajectory tracking experiment of an unmanned helicopter and anti-interference experiments.The controllers of unmanned helicopter are designed by PID control,fuzzy PID control and multi-dimensional Taylor network optimization control.The particle swarm optimization algorithm and the simple optimization algorithm are used to optimize the parameters of the controller designed by the three control methods,and the three controllers are brought to the best state.Compare the output of the three controllers.3.Disturbance was added to the unmanned helicopter mathematical model as well.Based on this,the control effects of the three control methods were compared,taking wind interference as an example,the wind interference experiment is carried out,and the anti-interference ability of the three control methods is shown.The interference experiments show that the multi-dimensional Taylor network optimal control has the best anti-interference ability,followed by fuzzy PID control,and PID has the worst performance among the three.4.Finally,summarize the work done on the research of unmanned helicopters and the application effect of multi-dimensional Taylor network optimal control on the rotorcraft represented by helicopter.