Research On Intelligent Control Algorithm Of Quadrotor UAV Under Uncertain Environments

In consideration of simple structure,vertical take-off,flexible mobility,and stable hovering,quadrotor unmanned aerial vehicle(QUAV)has broad prospects in the fields of defense military,industrial production,and life entertainment in recent years.However,the QUAV is a typical underactuated system with high nonlinearity,strong coupling and multivariable,and is vulnerable to various uncertainties,such as time-varying wind disturbance,model uncertainty,actuator fault,input saturation,low-accuracy state detection,input delay,and so on,which greatly increases the difficulty of model establishment and controller design.The QUAV system can be divided into attitude and position subsystems,in which the former ensures high-performance attitude stabilization,while the latter achieves high-precision trajectory tracking but depends on the control performance of the former.It should be pointed out that the existing results still have some shortcomings,such as slow convergence speed,chattering phenomenon,singular problem,poor robustness,strong constraints and few uncertain factors considered.Based on this,our goal is to design the high-performance intelligent control strategy to address the shortcomings of the existing results.The major contents are as follows:1.Firstly,the basic characteristics of QUAV are described in detail.Subsequently,the earth and body coordinate frames of QUAV and the conversion formula between the two coordinate frames are established.Based on Newton Euler Lagrange equation,the QUAV dynamics is constructed with consideration of external disturbances and system nonlinearities,which lays a thorough grounding for the following study of control algorithms.2.For the attitude control problem of QUVA with natural wind disturbance and input saturation,a finite-time extended state observer to address the effect of natural wind disturbance and estimate the information of the attitude angular velocity is constructed.Based on this,by using the non-singular terminal sliding mode manifold and the constructed auxiliary dynamic system,an anti-saturation finite-time attitude controller is proposed to obtain fast convergence rate,singularity restrain,and chattering elimination.Meanwhile,it can be proved that the tracking errors converge to sufficiently small bounded regions in finite time.3.Based on powerful nonlinear approximation ability of neural networks(NNs),the developed adaptive finite-time NN observer can effectively estimate the information of attitude angular velocity.Subsequently,an adaptive fuzzy sliding mode attitude controller is proposed via the triangular membership function and the centroid defuzzification method so that the lumped disturbance can be addressed effectively.In particular,the presented fuzzy controller can solve the problem of many fuzzy rules existing in the traditional fuzzy controller.In addition,the attitude controller includes an auxiliary dynamic system with singularity avoidance and does not contain discontinuous switching terms,which is conducive to eliminating the input saturation and suppressing the system chattering.4.The designed robust exact differentiator with strong robustness is insensitive to high-frequency noise and can realize effective estimation of velocity signals.Then,for the position and attitude control problem of QUAV with strong coupling,the designed adaptive NN attitude controller with low computation can realize the purposes of fault-tolerance,saturation suppression and anti-interference,and guarantee that the tracking errors in the closed-loop system approach near zero within finite time.More importantly,the designed control scheme can effectively reduce the number of adaptive parameters in the NN,which is beneficial to ease the computational burden of the control system.5.To deal with the problem of QUAV with input delay,this study firstly uses Pade approximation technology to mathematically transform the input delay.Then,by designing a fixed-time disturbance observer,various uncertain factors can be solved under the same control framework.In particular,the designed observer not only does not require the disturbance and its derivative to be bounded but also can ensure that the observation error converges to zero within a fixed time.On basis of this,an antisaturation controller based nonsingular fixed sliding mode is proposed and the global fixed time stability of the closed-loop system is proved,where the convergence time is not only bounded but also independent of the initial states.Extensive comparative simulations and numerical performance analysis are given to verify the effectiveness and superiority of the designed control methods.