Modeling and Robust Backstepping Sliding Mode Control with Adaptive RBFNN for a Novel Coaxial Eight-rotor UAV

This paper focuses on the robust attitude control of a novel coaxial eight-rotor unmanned aerial vehicles(UAV) which has higher drive capability as well as greater robustness against disturbances than quad-rotor UAV. The dynamical and kinematical model for the coaxial eight-rotor UAV is developed, which has never been proposed before. A robust backstepping sliding mode controller(BSMC) with adaptive radial basis function neural network(RBFNN) is proposed to control the attitude of the eightrotor UAV in the presence of model uncertainties and external disturbances. The combinative method of backstepping control and sliding mode control has improved robustness and simplified design procedure benefiting from the advantages of both controllers. The adaptive RBFNN as the uncertainty observer can effectively estimate the lumped uncertainties without the knowledge of their bounds for the eight-rotor UAV. Additionally, the adaptive learning algorithm, which can learn the parameters of RBFNN online and compensate the approximation error, is derived using Lyapunov stability theorem. And then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the novel coaxial eight-rotor UAV in the case of model uncertainties and external disturbances.

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.

Second order sliding mode control with back stepping approach for moving mass spinning missiles

An attitude controller using the second order sliding mode control methodology with a backstepping approach（SOSMCB）is designed and implemented for a spinning missile with two internal moving mass blocks.The system consists of a rigid body and two radial internal moving mass blocks and its mathematical model is established based on Newtonian mechanics.The control scheme integrates a second order sliding mode control algorithm into the last step of the backstepping approach,and its stability is proved by means of a Lyapunov function.The performance of the controller is demonstrated by numerical simulations,the results show that the attitude controller is stable and effective.

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.

Observer-based adaptive sliding mode backstepping output-feedback DSC for spin-stabilized canard-controlled projectiles

This article presents a complete nonlinear controller design for a class of spin-stabilized canard-controlled projectiles.Uniformly ultimate boundedness and tracking are achieved,exploiting a heavily coupled,bounded uncertain and highly nonlinear model of longitudinal and lateral dynamics.In order to estimate unmeasurable states,an observer is proposed for an augmented multiple-input-multiple-output（MIMO） nonlinear system with an adaptive sliding mode term against the disturbances.Under the frame of a backstepping design,an adaptive sliding mode output-feedback dynamic surface control（DSC） approach is derived recursively by virtue of the estimated states.The DSC technique is adopted to overcome the problem of ‘‘explosion of complexity＂ and relieve the stress of the guidance loop.It is proven that all signals of the MIMO closed-loop system,including the observer and controller,are uniformly ultimately bounded,and the tracking errors converge to an arbitrarily small neighborhood of the origin.Simulation results for the observer and controller are provided to illustrate the feasibility and effectiveness of the proposed approach.

ADAPTIVE BACKSTEPPING SLIDING MODE CONTROLLER FOR FLIGHT SIMULATOR BASED ON RBFNN

For flight simulator system,a kind of Adaptive Backstepping Sliding Mode Controller(ABSMC)based on Radial Base Function Neural Network(RBFNN)observer is presented.The sliding mode control theory is famous by its characteristic that it is insensitive to the external disturbances and parameters uncertainties.Combining this characteristic with Backstepping method can simplifies the controller design.And the addition of the terminal attractor can make the arrival time shorten greatly.However,too large external disturbances and parameters uncertainties are still not allowed to the system,and the design process of ABSMC does not have the upper bound information of disturbance until a RBFNN observer is designed to solve the problems.The simulation results show that the proposed scheme can improve the tracking precision and reduce the chattering of the control input,and the system has a higher robustness.

Group Coevolution and Immigration Pigeon-Inspired Optimized Dual-layer Controller for Aerial Manipulator Trajectory Tracking

The aerial manipulator expands the scope of unmanned aerial vehicle(UAV)'s application as well as increases the di±culties in the design of the controller.To better control the aerial manipulator for di®erent trajectories tracking under di®erent conditions,a new dual-layer controller is designed in this paper.The integral backstepping sliding mode controller(IBSMC)is applied to the outer-loop controller and backstepping controller(BC)is applied to the innerloop controller.To improve the performance of the system,an improved pigeon-inspired optimization(PIO)algorithm called group coevolution and immigration pigeon-inspired optimization(GCIPIO)algorithm is proposed to optimize the controller parameters of IBSMC.GCIPIO algorithm utilizes the group coevolution and immigration mechanisms.A series of simulations are conducted to show the advantage of the proposed method.The results illustrate that the proposed method ensures the closed-loop system has less end-e®ector tracking error.