Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties.The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller(MFISMC).A position controller is designed based on adaptive sliding mode control(SMC)to safely drive the aerial robot and ensure fast state convergence under external disturbances.Additionally,the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots.Then,the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state.Finally,to demonstrate the performance and robustness of the proposed control strategy,numerical simulations are carried out,which are also compared with other conventional strategies,such as proportional-integralderivative(PID),backstepping(BS),and SMC.The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

A Novel Disturbance Observer Based Fixed-Time Sliding Mode Control for Robotic Manipulators With Global Fast Convergence

This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems.Then an adaptive scheme is used and the adaptive FTDO(AFTDO) is developed,so that the priori knowledge of the lumped disturbance is not required.Further,a new non-singular fast terminal sliding mode(NFTSM) surface is designed by using an arctan function,which helps to overcome the singularity problem and enhance the robustness of the system.Based on the estimation of the lumped disturbance by the AFTDO,a fixed-time non-singular fast terminal sliding mode controller(FTNFTSMC)is developed to guarantee the trajectory tracking errors converge to zero within a fixed time.The settling time is independent of the initial state of the system.In addition,the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method.Finally,the fixed-time NFESM(FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers(SMCs) are performed.The comparative results confirm that the FTNFTSMC has superior control performance.

Control of trajectory tracking of two-wheeled differential spherical mobile robot

This paper presents a two-wheeled differential spherical mobile robot in view of the problems that the motion of spherical robot is difficult to control and the sensor is limited by the spherical shell.The robot is simple in structure,flexible in motion and easy to control.The kinematics and dynamics model of spherical mobile robot is established according to the structure of spherical mobile robot.On the basis of the adaptive neural sliding mode control,the trajectory tracking controller of the system is designed.During the simulation of the s-trajectory and circular trajectory tracking control of the spherical mobile robot,it is concluded that the spherical mobile robot is flexible in motion and easy to control.In addition,the simulation results show that the adaptive neural sliding mode control can effectively track the trajectory of the spherical robot.The adaptive control eliminates the influence of unknown parameters and disturbances,and avoids the jitter of left and right wheels during the torque output.

Robust chattering-free sliding mode control of space robot in task space

This paper studies the tracking control problem of a free-floating space robot in a task space. Considering the model uncertainties and external disturbance, a robust sliding mode controller is proposed using the Lyapunov direct method and dissipative theory. To eliminate the chattering phenomenon, an radial basis function （RBF） neural network is applied to replace the discontinuous part of the control signal. A novel on-line learning method of the weights and parameters of the RBF neural network established using Lyapunov function assures the stability of the system. It is proved that the proposed controller can guarantee that the L2 gain from disturbance to tracking error is lower than the given index y. Simulation results show that the control method is valid.

Feedback Attitude Sliding Mode Regulation Control of Spacecraft Using Arm Motion

The problem of spacecraft attitude regulation based on the reaction of arm motion has attracted extensive attentions from both engineering and academic fields.Most of the solutions of the manipulator’s motion tracking problem just achieve asymptotical stabilization performance,so that these controllers cannot realize precise attitude regulation because of the existence of non-holonomic constraints.Thus,sliding mode control algorithms are adopted to stabilize the tracking error with zero transient process.Due to the switching effects of the variable structure controller,once the tracking error reaches the designed hyper-plane,it will be restricted to this plane permanently even with the existence of external disturbances.Thus,precise attitude regulation can be achieved.Furthermore,taking the non-zero initial tracking errors and chattering phenomenon into consideration,saturation functions are used to replace sign functions to smooth the control torques.The relations between the upper bounds of tracking errors and the controller parameters are derived to reveal physical characteristic of the controller.Mathematical models of free-floating space manipulator are established and simulations are conducted in the end.The results show that the spacecraft’s attitude can be regulated to the position as desired by using the proposed algorithm,the steady state error is 0.000 2 rad.In addition,the joint tracking trajectory is smooth,the joint tracking errors converges to zero quickly with a satisfactory continuous joint control input.The proposed research provides a feasible solution for spacecraft attitude regulation by using arm motion,and improves the precision of the spacecraft attitude regulation.

Robust BELBIC-Extension for Trajectory Tracking Control

In real-life trajectory tracking applications of robotic manipulators uncertain robot dynamics, external disturbances and switching constraints which cannot be accommodated for by a conventional controller affect the system performance. We suggested an additional control element combining sliding mode and bio-mimetic, neurologically-inspired BELBIC （brain emotional learning-based intelligent control）. The former is invariant to internal and external uncertainties and guarantees robust behavior. The latter is based on an interplay of inputs relating to environmental information through error-signals of position and sliding surfaces and of emotional signals regulating the learning rate and adapting the future behaviour based on prior experiences and with the goal to maximize a reward function. We proofed the stability and the performance of the suggested control scheme through Lyapunov theory and numerical simulations, respectively.

Robust Finite-Time Trajectory Tracking Control of Wheeled Mobile Robots with Parametric Uncertainties and Disturbances

In this paper, a robust finite-time tracking control scheme is proposed for wheeled mobile robots with parametric uncertainties and disturbances. To eliminate the effect of lumped uncertainties,a nonlinear extended state observer(NESO) is employed to estimate the unknown states as well as uncertainties, and the corresponding coefficients are tuned via pole placement technique. Based on the observation values, the finite-time sliding mode controller is presented to guarantee that both the sliding mode variables and tracking errors converge to zero within finite time. Simulation results are given to demonstrate the effectiveness of the proposed control method.

Decentralized adaptive sliding mode control of a space robot actuated by control moment gyroscopes

An adaptive sliding mode control （ASMC） law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot. Each joint of the system is a free ball joint capable of rotating with three degrees of freedom （DOF）. A cluster of control moment gyroscopes （CMGs） is mounted on each link and the base to actuate the system. The modified Rodrigues parameters （MRPs） are employed to describe the angular displacements, and the equations of motion are derived using Kane＇s equations. The controller for each link or the base is designed sep- arately in decentralized scheme. The unknown disturbances, inertia parameter uncertainties and nonlinear uncertainties are classified as a ＂lumped＂ matched uncertainty with unknown upper bound, and a continuous sliding mode control （SMC） law is proposed, in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty. A gen- eral amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input. Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov＇s method. Simulation results based on a three-link system verify the effectiveness of the proposed controller.

Precise trajectory tracking of mecanum-wheeled omnidirectional mobile robots via a novel fixed-time sliding mode control approach

This paper proposes a novel fixed-time sliding mode control approach for trajectory-tracking tasks of a mecanum-wheeled omnidirectional mobile robot.First,the idea of two-phase attractors is introduced into the domain of sliding mode control,and a new fixed-time sliding surface is proposed.Then,according to this sliding surface,a new type of nonsingular fast terminal sliding mode control algorithm is designed for the omnidirectional mobile robot,which can realize a fast fixed-time convergence property.The stability of the control system is proven scrupulously,and a guideline for control-parameter tuning is expounded.Finally,experiments are implemented to test the trajectory-tracking performance of the robot.Experimental results demonstrate the superiority of the proposed sliding surface and the corresponding control scheme in comparison with benchmark controllers.

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.

基于改进非线性滑模控制的轮式机器人轨迹跟踪

针对轮式机器人的轨迹跟踪控制存在的问题,设计了一种改进非线性快速终端滑模控制器(improved nonlinear fast terminal sliding mode controller,INFTSMC)的控制方案。首先,通过对轮式机器人运动学的分析建立了轨迹跟踪误差模型;其次,在设计滑模控制器阶段,针对非线性快速终端滑模控制器存在奇异点,采用一种新的滑模面幂指数时变策略来设计非奇异终端滑模控制器,解决了非线性快速终端滑模控制器奇异问题,通过构造Lyapunov函数进行稳定性分析证明了该策略的稳定性,并且进行收敛时间分析给出系统从任意初始状态收敛至平衡点所需要的时间;然后,在新的滑模面幂指数时变策略的基础上设计了轮式机器人线速度和角速度控制律,使得轮式机器人轨迹跟踪误差快速收敛至0,实现了移动机器人对期望轨迹的快速跟踪。通过仿真实验与非线性快速终端滑模控制器和传统滑模控制其进行对比,验证了改进非线性快速终端滑模控制器的优越性。

考虑输入饱和的机械臂轨迹跟踪滑模控制

针对复合干扰和输入饱和特性影响机械臂轨迹跟踪精度的问题,给出了一种基于输入饱和补偿的自适应积分滑模控制策略。首先,基于自适应控制方法设计了辅助函数,以消除输入饱和特性的影响;其次,利用所估计的复合干扰上限,结合非奇异积分终端滑模控制方法设计轨迹跟踪控制律,使跟踪误差快速收敛至零的邻域,且削弱了抖振,经过Lyapunov稳定性定理的证明,该算法可以保证轨迹跟踪误差的有限时间收敛性;最后,通过仿真与实验手段,与自适应非奇异快速终端滑模控制方法的对比验证了所提控制方法的有效性。结果表明:机械臂各关节在仿真和实验中分别可以在0.5 s和0.8 s内跟踪上期望轨迹,跟踪误差能降低到1.2×10^(-3)rad和8.7×10^(-3)rad内,有效解决机械臂输入饱和问题和复合干扰对系统轨迹跟踪控制精度的影响。

一种新型3-RRPU并联机构的运动学及鲁棒控制研究

针对现有的三平移并联机构大多正解不唯一、较难实现精确稳定运动控制的问题,提出了一种新的3-RRPU型三平移并联机构,同时研究了机构的运动学、动力学及轨迹跟踪控制方法。首先,运用螺旋理论分析了该机构三平移的原理,进行了驱动输入的选取与论证,对机构平台奇异性、驱动奇异性和支链奇异性进行了分析;其次,运用运动学理论建立了运动学模型,推导了位置正、逆解析解;再次,运用拉格朗日动力学理论建立了机构操作空间的刚体动力学模型;最后,提出了一种基于非线性反馈解耦的自适应滑模轨迹跟踪控制方法,以证明其控制稳定性,并基于动力学模型对空间轨迹跟踪精度和控制力矩进行了仿真分析。研究结果表明:3-RRPU并联机构的位置正解在一般位形下具有唯一性,机构的平台奇异位形和驱动奇异位形少且无支链奇异。该轨迹控制方法可使机构在载荷20 kg、速度0.18 m/s、加速度0.12 m/s 2下,实现0.002 m以内的高精度复杂轨迹跟踪;基于Sigmoid函数的轨迹控制方法还能有效削弱控制力矩的抖振,为实现工业领域高速、高精度、高性能的三平移运动提供了新方法。

基于双环自适应滑模的移动机器人轨迹跟踪控制

为了提升移动机器人轨迹跟踪精度,针对传统双环控制内外环协调性差、抗扰性弱的问题,文章提出双环自适应滑模的控制方法。为消除传统滑模控制(sliding mode control, SMC)方法中的趋近阶段,设计新型时变积分终端滑模控制器以保证系统状态始终位于滑模面,并通过控制器参数调节实现内环姿态误差和外环位置误差的快速收敛;构建基于势垒函数的增益调控方法,保证在扰动上界未知的情况下有效地抑制状态抖振,提高轨迹跟踪系统的抗干扰能力。对所提方法进行的验证分析结果表明,相较于现有的双环控制方法,该文轨迹跟踪控制方法精度更高、鲁棒性更强。

铆接机器人位置和压铆力自适应模糊滑模阻抗控制

针对机器人铆接小尺寸、低刚度铆钉过程中对准精度要求高、作业行程小和冲击力大等问题,提出了一种结合自适应模糊滑模控制和模糊阻抗控制的机器人铆接控制方法。为此,将机器人铆接控制过程分为接近对准与压铆两个阶段。其中,为了实现快速接近铆钉顶部以及铆接头与铆钉轴线的精确对准,设计了以双曲正切函数为切换函数的模糊自适应滑模控制器,使得切换过程更加光滑、滑模增益自适应调节,从而降低了系统的抖振,实现了运动的快速性和准确性;针对压铆阶段作业行程小、冲击力大的特点,设计了以接触力误差和力增量为输入的阻尼调整模糊控制器,减少了阻尼参数在阻抗控制过程中产生的振荡,避免了过度力加载导致的铆钉损坏或铆接失败。仿真及试验结果表明,所给出的控制方法位置精度在0.3 mm以内,力接触具有更好的稳定性、实时性和快速性,能够满足铆接工艺规范要求,对于铆接机器人的高精度作业具有借鉴意义。

多算法融合的并联食品分拣机器人轨迹跟踪控制方法

目的:解决并联食品分拣机器人轨迹跟踪控制方法存在的控制精度低和运动稳定性差等问题。方法:在四自由度并联机器人结构基础上,提出将滑模控制算法、模糊控制算法和改进蝙蝠算法相结合用于并联食品分拣机器人轨迹跟踪控制。通过改进蝙蝠算法对模糊算法带宽进行寻优,通过优化的模糊控制算法自适应调整滑膜控制算法的模糊增益和滑膜面斜率,降低控制器的跟踪误差,提高抗干扰能力,并验证所提轨迹跟踪控制方法的优越性。结果:所提轨迹跟踪控制方法实际分拣准确率为99.90%,平均分拣时间为0.509 s。结论:与常规方法相比,所提轨迹跟踪控制方法的关节轨迹跟踪精度更高,抗干扰能力更强,输出力矩更加平滑。

基于自适应分数阶滑模的机械臂轨迹跟踪控制

针对机械臂轨迹控制过程中受建模误差、外部时变干扰等因素的影响,导致控制精度下降的问题,提出了一种自适应分数阶滑模控制方法。首先设计了一种新型的分段趋近律,并基于所提出的分数阶滑模面和自适应技术,设计了复合控制器,以保证有效应对系统扰动,快速趋近滑模面并削弱机械臂的抖振;其次证明了系统的闭环稳定性和有限时间收敛性;最后通过仿真实验验证了所提方法在机械臂轨迹跟踪中的快速性和精准性。

涂覆并联机器人轨迹跟踪同步控制策略研究

当涂覆并联机器人两侧分支不同步或从主动关节到末端执行器存在运动传递误差时,会影响机器人的轨迹跟踪性能。为此,提出一种结合深度学习的智能跟踪滑模同步控制方法(ITSSMSC)。基于复合误差设计滑动面,利用深度学习算法训练具有多隐层的深度神经网络,在不调整额外参数的情况下跟踪由不同涂层工艺要求决定的任意给定轨迹,并保证同步性能。最后,通过实验验证了该控制方法的有效性。结果表明:该控制方法在不同期望轨迹下均能实现良好的跟踪控制性能和同步性能。

基于LESO的轮式移动机器人滑模轨迹跟踪控制

针对轮式移动机器人在车轮打滑情况下的轨迹跟踪控制问题,提出了一种利用线性扩张状态观测器(Linear Extended State Observer,LESO)和积分滑模面的控制方案。首先,根据车轮打滑情况下的非完整约束条件建立轮式移动机器人的运动学模型。根据动能函数和拉格朗日方程建立其动力学模型。将这两种模型相结合得到力矩与速度相关的数学模型。其次,利用LESO对该数学模型进行扩张,并对总扰动进行估计。基于实际速度与虚拟速度之差设计带有积分项的滑模面,将扰动估计值前馈结合滑模面设计动力学控制器,并给出速度跟踪误差在有限时间内收敛的证明。最后,与基于超螺旋干扰观测器设计的控制方案仿真相比,所提出方案角速度跟踪误差在1 s左右时已趋于零,车轮力矩值稳定在3 N·m左右,且无锯齿抖动,扰动误差在1~5 s时波动更小,5~20 s时未出现明显锯齿抖动,仿真结果表明所提方案跟踪效果更好,抗干扰能力更强,观测精度更高。