Tradeoff Analysis of Factors Affecting Longitudinal Carrier Landing Performance for Small UAV Based on Backstepping Controller

Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.

Adaptive Backstepping Control Design for Semi-Active Suspension of Half-Vehicle With Magnetorheological Damper

This paper investigates the problem of controlling half-vehicle semi-active suspension system involving a magnetorheological(MR)damper.This features a hysteretic behavior that is presently captured through the nonlinear Bouc-Wen model.The control objective is to regulate well the heave and the pitch motions of the chassis despite the road irregularities.The difficulty of the control problem lies in the nonlinearity of the system model,the uncertainty of some of its parameters,and the inaccessibility to measurements of the hysteresis internal state variables.Using Lyapunov control design tools,we design two observers to get online estimates of the hysteresis internal states and a stabilizing adaptive state-feedback regulator.The whole adaptive controller is formally shown to meet the desired control objectives.This theoretical result is confirmed by several simulations demonstrating the supremacy of the latter compared to the skyhook control and passive suspension.

A New Robust Adaptive Neural Network Backstepping Control for Single Machine Infinite Power System With TCSC

For a single machine infinite power system with thyristor controlled series compensation(TCSC) device, which is affected by system model uncertainties, nonlinear time-delays and external unknown disturbances, we present a robust adaptive backstepping control scheme based on the radial basis function neural network(RBFNN). The RBFNN is introduced to approximate the complex nonlinear function involving uncertainties and external unknown disturbances, and meanwhile a new robust term is constructed to further estimate the system residual error,which removes the requirement of knowing the upper bound of the disturbances and uncertainty terms. The stability analysis of the power system is presented based on the Lyapunov function,which can guarantee the uniform ultimate boundedness(UUB) of all parameters and states of the whole closed-loop system. A comparison is made between the RBFNN-based robust adaptive control and the general backstepping control in the simulation part to verify the effectiveness of the proposed control scheme.

Wave Heave Compensation Based on An Optimized Backstepping Control Method

The vessel heave motion caused by wave action increases the difficulty of installing offshore wind equipment.On-board wave heave compensation devices have therefore become increasingly critical in ensuring the stability and safety of the gangway and working platform.This study accordingly improves the compensation effect of such devices by developing a wave heave compensation model and designing an optimized backstepping control method.First,a model of the compensation system including the servo motor and electric cylinder is established by using the mechanism method.Second,a backstepping control method is designed to track the vessel heave motion,and particle swarm optimization is applied to optimize the control parameters.Finally,MATLAB/Simulink is used to simulate the application of the optimized backstepping controller,then regular and irregular heave motions are applied as input to a Stewart platform to evaluate the effectiveness of the control method.The experimental results show that the compensation efficiency provided by the proposed optimized backstepping control method is larger than 75.0%.

Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System

Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking perfor-mance.To deal with these difficulties,this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interfer-ence ability.For this purpose,the nonlinear dynamic model is firstly established,where the nonlinear behaviors and modeling uncertainties are lumped as one term.Then,the extended state observer is introduced to estimate the lumped distur-bance.The system stability is proved by using the Lyapunov stability theorem.Finally,comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.

Adaptive Backstepping Tracking Control of a 6-DOF Unmanned Helicopter

This paper presents an adaptive backstepping control design for a class of unmanned helicopters with parametric uncertainties. The control objective is to let the helicopter track some pre-defined position and yaw trajectories. In order to facilitate the control design, we divide the helicopter s dynamic model into three subsystems. The proposed controller combines the backstepping method with online parameter update laws to achieve the control objective. The global asymptotical stability(GAS) of the closed-loop system is proved by a Lyapunov based stability analysis. Numerical simulations demonstrate that the controller can achieve good tracking performance in the presence of parametric uncertainties.

Adaptive backstepping control of tracked robot running trajectory based on real-time slip parameter estimation

To ensure the stable driving of tracked robots in a complex farmland environment,an adaptive backstepping control method for tracked robots was proposed based on real-time slip parameter estimation.According to the kinematics analysis method,the kinematic model of the tracked robot was established,and then,its pose error differential equation was further obtained.On this basis,the trajectory tracking controller of the tracked robot was designed based on the backstepping control theory.Subsequently,according to the trajectory tracking error of the tracked robot,the back propagation neural network(BPNN)was used to adaptively adjust the control parameters in the backstepping controller,and the inputs of the BPNN are the trajectory tracking error xe,ye,θe.After that,the soft-switching sliding mode observer(SSMO)was designed to identify the slip parameters during the running of the tracked robot.And then the parameters were compensated into the adaptive backstepping controller to reduce the trajectory tracking error.The simulation results show that the proposed adaptive backstepping control method with SSMO can improve the accuracy of the trajectory tracking control of the tracked robot.Additionally,the designed SSMO can accurately estimate the slip parameters.

A Comparative Study of Synchronization Methods of Rucklidge Chaotic Systems with Design of Active Control and Backstepping Methods

The performance of two widely used chaos synchronization approaches, active control and backstepping control, is investigated in this study. These two methods are projected to synchronize two chaotic systems (Master/Drive of Rucklidge Systems) that are identical but have different initial conditions. The paper’s significant feature is that based on error dynamics, controllers are designed using the appropriate variable and the time synchronization between master Rucklidge and drive Rucklidge systems using both methods. The control function of the active control method is designed on the proper selection of matrices. The chaotic behavior is controlled using a recursive backstepping design based on the Lyapunov stability theory with a validated Lyapunov function. The effectiveness of the controller in eradicating the chaotic behavior from the state trajectories is also revealed using numerical simulations with Matlab. The backstepping method is superior to the active control method for synchronization of the measured pair of systems, as it takes less time to synchronize while exhausting the first one than the second one with great performance, according to numerical simulation and graphical outcomes.

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.

Backstepping adaptive control of hydraulic Stewart platform using dynamic surface

Hydraulic Stewart platform is characterized by nonlinearity for driving system in essence,severe load coupling among the legs,which bring a great difficulty for controller design and performance improvement.Afore controller research is either low in tracking performance and movement smoothness when it ignores the nonlinearity and dynamics coupling,or complex in algorithm and has the need of acceleration feedback or observer when the dynamics coupling and nonlinearity is included.To solve the dilemma,a new controller,backstepping adaptive control of hydraulic Stewart platform using dynamic surface is put forward based on the complete dynamics including the upper platform dynamics and hydraulic nonlinearity in driving system.Asymptotic stability of the whole system is proved by Lyapunov method.The proposed algorithm is simple by avoiding the use of acceleration.The simulation results indicate that the control algorithm performs better than the normal PID controller in control precision,dynamic response and depression of the cross coupling.

Backstepping Adaptive Controller of Electro-Hydraulic Servo System of Continuous Rotary Motor

In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance,the design method of backstepping adaptive controller is put forward.The mathematical model of electro-hydraulic servo system of continuous rotary motor is established,and the whole system is decomposed into several lower order subsystems,and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory,an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability,and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor,and the proposed control strategy is feasible.

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.

Robust Tracking Control of Uncertain MIMO Nonlinear Systems with Application to UAVs

In this paper, we consider the robust adaptive tracking control of uncertain multi-input and multi-output(MIMO) nonlinear systems with input saturation and unknown external disturbance. The nonlinear disturbance observer(NDO)is employed to tackle the system uncertainty as well as the external disturbance. To handle the input saturation, an auxiliary system is constructed as a saturation compensator. By using the backstepping technique and the dynamic surface method,a robust adaptive tracking control scheme is developed. The closed-loop system is proved to be uniformly ultimately bounded thorough Lyapunov stability analysis. Simulation results with application to an unmanned aerial vehicle(UAV) demonstrate the effectiveness of the proposed robust control scheme.

Control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton.To improve the detection accuracy of the humanrobot interaction torque,a BPNN(backpropagation neural networks)is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor.Meanwhile,the backstepping controller is designed to realize the exoskeleton's passive position control,which means that the person passively adapts to the exoskeleton.On the other hand,a variable admittance controller is used to implement the exoskeleton's active followup control,which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance.To improve the wearable comfortable effect,serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters.Finally,the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

Adaptive Containment Control for Fractional-Order Nonlinear Multi-Agent Systems With Time-Varying Parameters

This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and disturbances.By using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is overcome.The command filter is introduced to solve the complexity problem inherent in adaptive backstepping control.Meanwhile,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is utilized.Then,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the leaders.Based on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic convergence.Finally,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.

Contribution to the Control and Command of a Quadrirotor with Six Degrees of Freedom in an Urban Environment

The objective of this article is to make a contribution relating to the modeling, control, simulation and stabilization of a complex system, with six degrees of freedom of a particular drone which presents many advantages and challenges. On the technological, military, political and other levels with an enormous and beneficial social contribution, it is a quadrotor which is a nonlinear, strongly coupled and unstable system. Such a structure is difficult to master, because the control is multivariable in the sense that six degrees of freedom are to be controlled simultaneously and operating in an environment subject to disturbances. Two commands, in particular Backstepping and PID, will be applied to obtain the stabilization of the quadcopter at the desired values, in attitude and in altitude. This article presents the comparative results of the performance of the quadcopter under the two controls. The effect of the parameters of each command on the response time of the system is elucidated under the Matlab/Simulink environment. For a simulation time of up to 10 seconds minimum with a less good response time of almost 2 seconds for the PID control, these results prove the robustness of the Backstepping command.

基于反演积分技术的无人驾驶水面飞行器的自动驾驶仪设计及其实验结果

Controller tuning is the correct setting of controller parameters to control complex dynamic systems appropriately and with high accuracy.Therefore,this study addressed the development of a method for tuning the heading controller of an unmanned surface vehicle(USV)based on the backstepping integral technique to enhance the vehicle behavior while tracking a desired position for water monitoring missions.The vehicle self-steering system(autopilot system)is designed theoretically and tested via a simulation.Based on the Lyapunov theory,the stability in the closed-loop system is guaranteed,and the convergence of the heading tracking errors is obtained.In addition,the designed control law is implemented via a microcontroller and tested experimentally in real time.Conclusion,experimental results were carried out to verify the robustness of the designed controller when disturbances and uncertainties are introduced into the system.

Vibration Control of A Flexible Marine Riser System Subject to Input Dead Zone and Extraneous Disturbances

An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.

Command filtered integrated estimation guidance and control for strapdown missiles with circular field of view

In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.

A Stator Current Vector Orientation Based Multi-objective Integrative Suppressions of Flexible Load Vibration and Torque Ripple for PMSM Considering Electrical Loss

To store energy from the grid into spiral torsion spring(STS)smoothly and efficiently via PMSM,a multi-objective control problem of flexible load’s vibration,PMSM’s torque ripple,and electrical loss is raised,where the current studies on vibration and torque ripple are mostly addressed separately,not to mention electrical loss.This research attempts to propose a multi-objective integrative control scenario that can simultaneously solve these problems satisfactorily in a unitary nonlinear control framework.Firstly,a dynamic mathematical model of PMSM is built under stator current vector orientation,and then the model of PMSM is combined with the vibration model of STS to establish the overall system model of STS driven by PMSM with considering motor’s electrical loss.Then,a backstepping control principle-based multi-objective integrative control approach is proposed to realize the suppression of flexible load’s vibration and the reduction of PMSM’s torque ripple and electrical loss concurrently.Meanwhile,this research also designs a wide range speed identification method based on the least square algorithm with a forgetting factor.Simulation and experimental results have verified that the proposed integrative control method enables the state variables to track their respective references quickly and accurately,both torque ripple and load vibration are effectively suppressed,and the operating efficiency of the whole system is improved.