Backstepping sliding mode control with self recurrent wavelet neural network observer for a novel coaxial twelve-rotor UAV

The robust attitude control for a novel coaxial twelve-rotor UAV which has much greater payload capacity,higher drive capability and damage tolerance than a quad-rotor UAV is studied. Firstly,a dynamical and kinematical model for the coaxial twelve-rotor UAV is designed. Considering model uncertainties and external disturbances,a robust backstepping sliding mode control( BSMC) with self recurrent wavelet neural network( SRWNN) method is proposed as the attitude controller for the coaxial twelve-rotor. A combinative algorithm of backstepping control and sliding mode control has simplified design procedures with much stronger robustness benefiting from advantages of both controllers. SRWNN as the uncertainty observer is able to estimate the lumped uncertainties effectively.Then the uniformly ultimate stability of the twelve-rotor system is proved by Lyapunov stability theorem. Finally,the validity of the proposed robust control method adopted in the twelve-rotor UAV under model uncertainties and external disturbances are demonstrated via numerical simulations and twelve-rotor prototype experiments.

A switching-based backstepping sliding mode control for space manipulator in presence of gravity variation

A novel switching-based backstepping sliding mode control(SBSMC) scheme is devised for the space manipulator exposed to different gravity.With a view to distinct differences in dynamics properties when the operating conclition of space manipulator changer,the space manipulator can be thought of as a system composed of two subsystems,the ground subsystem and the space subsystem.Two different types of backstepping sliding mode(BSM) controllers are designed,one is suited for the ground subsystem and the other is for the space one.The switching between two subsystems can be implemented automatically when the switching mechanism is triggered,and the controllers for their subsystems experience synchronous switching.In this way,the space manipulator always has good behaviors in trajectory tracking.Moreover,multi-Lyapunov functions are introduced to prove the stability of this switching approach.According to simulation results,the method constructed in this research has better performance in control precision and adaptability compared with proportional-derivative(PD) control.

Modeling and robust adaptive control for a coaxial twelve-rotor UAV

Compared with the quad-rotor unmanned aerial vehicle (UAV), the coaxial twelve-rotor UAV has stronger load carrying capacity, higher driving ability and stronger damage resistance. This paper focuses on its robust adaptive control. First, a mathematical model of a coaxial twelve-rotor is established. Aiming at the problem of model uncertainty and external disturbance of the coaxial twelve-rotor UAV, the attitude controller is innovatively adopted with the combination of a backstepping sliding mode controller (BSMC) and an adaptive radial basis function neural network (RBFNN). The BSMC combines the advantages of backstepping control and sliding mode control, which has a simple design process and strong robustness. The RBFNN as an uncertain observer, can effectively estimate the total uncertainty. Then the stability of the twelve-rotor UAV control system is proved by Lyapunov stability theorem. Finally, it is proved that the robust adaptive control strategy presented in this paper can overcome model uncertainty and external disturbance effectively through numerical simulation and prototype of twelve-rotor UAV tests.

Backstepping sliding mode control of a variable speed wind turbine for power optimization

To optimize the energy capture from the wind,wind turbine(WT)should operate at variable speed.Based on the wind speed,the operating regions of the WT are divided into two parts:below and above the rated wind speed.The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train.At above rated wind speed,the aim is to maintain the rated power by using pitch control.This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control(BSMC).In BSMC,generator torque is considered as the control input that depends on the optimal rotor speed.Usually,this optimal rotor speed is derived from effective wind speed.In this paper,effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon(MNR)algorithm.Initially,a conventional sliding mode controller(SMC)is applied to the WT,but the performance of the controller was found to be less robust with respect to disturbances.Generally,WT external disturbance is not predictable.To overcome the above drawback,BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue,aerodynamics,structures,and turbulence(FAST)WT simulator in the presence of disturbances.From the results,it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances.