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 Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.

Backstepping sliding mode control for uncertain strict-feedback nonlinear systems using neural-network-based adaptive gain scheduling

A neural-network-based adaptive gain scheduling backstepping sliding mode control（NNAGS-BSMC） approach for a class of uncertain strict-feedback nonlinear system is proposed.First, the control problem of uncertain strict-feedback nonlinear systems is formulated. Second, the detailed design of NNAGSBSMC is described. The sliding mode control（SMC） law is designed to track a referenced output via backstepping technique.To decrease chattering result from SMC, a radial basis function neural network（RBFNN） is employed to construct the NNAGSBSMC to facilitate adaptive gain scheduling, in which the gains are scheduled adaptively via neural network（NN）, with sliding surface and its differential as NN inputs and the gains as NN outputs. Finally, the verification example is given to show the effectiveness and robustness of the proposed approach. Contrasting simulation results indicate that the NNAGS-BSMC decreases the chattering effectively and has better control performance against the BSMC.

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.

Sliding mode control for an aerodynamic missile based on backstepping design

In order to solve the mismatched uncertainties of a class of nonlinearsystems, a control method of sliding mode control (SMC) based on the backstepping design isproposed. It introduces SMC in to the last step of backstepping design to modify the backsteppingalgorithm. This combination not only enables the generalization of the backstepping design to beapplied to more general nonlinear systems, but also makes the SMC method become effective in solvingthe mismatched uncertainties. The SMC based on the backstepping design is applied to the flightcontrol system design of an aerodynamic missile. The control system is researched throughsimulation. The simulation results show the effectiveness of the proposed control method.

Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.

Adaptive Backstepping Sliding Mode Control for Nonlinear Systems with Input Saturation

An adaptive backstepping sliding mode control is proposed for a class of uncertain nonlinear systems with input saturation.A command filtered approach is used to prevent input saturation from destroying the adaptive capabilities of neural networks (NNs).The control law and adaptive updating laws of NNs are derived in the sense of Lyapunov function,so the stability can be guaranteed even under the input saturation.The proposed control law is robust against the disturbance,and it can also eliminate the impact of input saturation.Simulation results indicate that the proposed controller has a good performance.

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.

Application of Adaptive Backstepping Sliding Mode Control in Alternative Current Servo System of Rocket Launcher

An adaptive backstepping sliding mode control approach is introduced to control the pitch motion of a rocket launcher. Its control law is proposed to guarantee that the control system is ultimately bounded in a Lyapunov sense and make the servo system track the instruction of reference position globally and asymptotically. In addition, the sliding mode control can restrain the effects of parameter uncertainties and external disturbance. The functions of adaptive mechanism and sliding mode control are analyzed through the simulation in the different conditions.The simulation results illustrate that the method is applicable and robust.

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.

Adaptive Backstepping Slide Mode Control of Pneumatic Position Servo System

With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental performance, as compared with some existing methods. results show that the designed controller can achieve better tracking

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.

Robust Graded Sliding Mode Tracking Control for Low Speed Spinning Ballistic Missiles

The nonlinear dynamic model of spinning ballistic missiles is established during the first boosting phase of the missile. Based on the conventional backstepping sliding mode control and the assumption of a two time-scale separation of missile dynamics, a graded sliding mode controller is designed with two sub-sliding surfaces which have invariability to external disturbances and parameter perturbations, and a matrix which comprises three first order low pass filters is introduced to prevent “explosion of terms”. Owing to the upper bounds of the uncertainties are difficult to obtain in advance, adaptive laws are introduced to estimate the values of the uncertainties in real-time. Eventually, the numerical simulation results given to show the proposed controller can ensure the steady flight of missiles.

Adaptive backstepping-based NTSM control for unmatched uncertain nonlinear systems

An adaptive backstepping-based non-singular termi- nal sliding mode （NTSM） control method is proposed for a class of uncertain nonlinear systems in the parameteric-strict feedback form. The adaptive control law is combined with the first n - 1 steps of the backstepping method to estimate the unknown pa- rameters of the system. In the nth step, an NTSM control strategy is utilized to drive the last state of the system to converge in a finite time. Furthermore, the derivate estimator is used to obtain the derivates of the states of the error system; the higher-order non-singular terminal sliding mode control （HONTSMC） law is de- signed to eliminate the chattering and make the system robust to both matched and unmatched uncertainties. Compared to the adaptive backstepping-based linear sliding mode control method （LSMC）, the proposed method improves the convergence rate and the steady-state tracking accuracy of the system, and makes the control signal smoother. Finally, the compared simulation results are presented to validate the method.

Modeling and controlling of a flexible hydraulic manipulator

A mathematical model was developed combining the dynamics of an Euler-Bernoulli beam, described by the assumed-mode method and hydraulic circuit dynamics. Only one matrix, termed drive Jacobian, was needed in the modeling of interaction between hydraulic circuit and flexible manipulator mechanism. Furthermore, a new robust controller based on mentioned above dynamic model was also considered to regulate both flexural vibrations and rigid body motion. The proposed controller combined sliding mode and backstepping techniques to deal with the nonlinear system with uncertainties. The sliding mode control was used to achieve an asymptotic joint angle and vibration regulation by providing a virtual force while the backstepping technique was used to regulate the spool position of a hydraulic valve to provide the required control force. Simulation results are presented to show the stabilizing effect and robustness of this control strategy.

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.

多关节工业机器人BSMC与EPCH协同优化控制

为了解决多关节工业机器人无法同时具有优越的快速性与准确性的问题,提出了反步滑模控制(BSMC)与误差端口受控哈密顿(EPCH)控制的协同优化控制策略。首先,分别设计了BSMC控制器与EPCH控制器;其次,采用基于机器人关节位置误差的高斯函数作为协同优化控制系数,使系统在BSMC与EPCH之间进行平滑切换,且进一步设计了协同优化控制策略,使多关节工业机器人能够兼具BSMC控制器与EPCH控制器的优点;最后,仿真实验结果表明,所提出的控制策略可以使机器人关节伺服系统同时具有快速的动态响应速度和准确的跟踪精度。

Robust backstepping global integral terminal sliding mode controller to enhance dynamic stability of hybrid AC/DC microgrids

In this paper,a Backstepping Global Integral Terminal Sliding Mode Controller(BGITSMC)with the view to enhancing the dynamic stability of a hybrid AC/DC microgrid has been presented.The proposed approach controls the switch-ing signals of the inverter,interlinking the DC-bus with the AC-bus in an AC/DC microgrid for a seamless interface and regulation of the output power of renewable energy sources(Solar Photovoltaic unit,PMSG-based wind farm),and Battery Energy Storage System.The proposed control approach guarantees the dynamic stability of a hybrid AC/DC microgrid by regulating the associated states of the microgrid system to their intended values.The dynamic stabil-ity of the microgrid system with the proposed control law has been proved using the Control Lyapunov Function.A simulation analysis was performed on a test hybrid AC/DC microgrid system to demonstrate the performance of the proposed control strategy in terms of maintaining power balance while the system’s operating point changed.Furthermore,the superiority of the proposed approach has been demonstrated by comparing its performance with the existing Sliding Mode Control(SMC)approach for a hybrid AC/DC microgrid.

基于PI建模和反步滑模控制的主动波浪补偿策略

海上起重船受风、浪、涌影响会产生剧烈的船舶姿态变化,造成起重机和货物的位姿变化,对货物和人员存在安全隐患,波浪补偿平台的稳定性控制能有效减少复杂海况下船舶运动对海上作业安全性、稳定性和精准性的影响,对浮式起重船海上设备精准装载作业极其重要。针对补偿平台的迟滞非线性导致的建模困难和控制不精确问题,本文提出基于PI(Prandtle–Ishlinskii)建模和反步滑模控制的主动波浪补偿策略。首先,通过实验得到补偿系统的迟滞效应曲线,分析系统迟滞环建立PI迟滞模型,并采用递推最小二乘法辨识模型的各个参数,从而求得系统模型。然后,基于李雅普诺夫(Lyapunov)稳定性设计反步控制补偿方法,并结合滑模控制规律加快初始控制速度。最后,将反步滑模法应用于补偿系统,采用MATLAB软件仿真在规则波和不规则波下的响应来验证算法和模型的正确性,并在工控机中用C#编写控制程序,驱动运动控制卡控制伺服电机带动电缸进行补偿运动,同时通过传感器采集系统运动的实时数据,并反馈给工控机形成闭环,以期验证补偿平台在补偿规则波和不规则波下的补偿效果。实验结果表明,所建立的斯图尔特(Stewart)浮式平台中,PI迟滞模型具有良好的精度,反步终端滑模控制算法在Stewart平台的实际控制中能够很好地补偿波浪运动,相比比例–积分–微分控制(PID)、反步法、强化学习等控制方法,反步终端滑模方法能快速较好跟踪期望位移,补偿精度达到0.9729。

基于改进反步滑模控制算法的拖轮自主靠泊控制

[目的]针对拖轮的自主靠泊控制问题,研究基于虚拟船领导的目标跟踪控制策略在拖轮自主靠泊中的应用。[方法]首先,将拖轮的自主靠泊过程转变为虚拟拖轮和实际拖轮的目标跟踪控制过程;然后,设计靠泊系统的运动学模型,考虑靠泊场景中的特殊环境干扰,使用反步法和滑模控制法(SMC)设计全回转尾推进拖轮的自主靠泊控制器,提供了3种不同的滑模面设计并使用李雅普诺夫函数进行稳定性验证;最后,采用仿真实验的方式,通过靠泊轨迹、速度误差和距离误差来对控制的效果进行验证。[结果]仿真实验结果表明,设计的拖轮自主靠泊控制策略以及控制器在拖轮自主靠泊场景中具有较好的效果,面对系统的不确定干扰有较好的表现。[结论]该控制策略以及靠泊控制器的适用性以及鲁棒性较好,以全新的角度实现了拖轮自主靠泊控制,为后续拖轮的靠泊控制研究提供了新的方向。