全局指数收敛的机器人PD 自适应轨迹跟踪

针对机器人轨迹跟踪,介绍一种新的ＰＤ自适应控制算法。该算法是全局按指数收敛的,直接利用期望轨迹,不需要定义虚拟参考轨迹,结构简单,计算量小;并能完全消除模型误差产生的轨迹误差,使有界不确定性干扰产生的轨迹误差任意小。两关节直接驱动机器人的实验研究证明了所提出算法的有效性。     

一种机器人轨迹的鲁棒跟踪控制

把基于拉格朗日方程的n关节机器人动力学模型,转化成了一线性状态方程.基于这种线性状态方程,利用李雅普诺夫函数方法分别针对机器人标称模型和有外界不确定性干扰时,设计前馈控制器和反馈控制器,使得机器人的实际运动轨迹在标称模型下,指数收敛于所给定的期望运动轨迹;在有外界不确定性干扰时,它与期望轨迹的误差是终值有界的.并且,针对后者所提出的控制律进行仿真.仿真结果表明,这种连续鲁棒控制律对于机器人系统存在外界不确定性干扰时是十分有效的.     

2-DOF绳索驱动并联机构轨迹跟踪控制

基于PD控制和前馈控制方法,对2-DOF的绳索驱动并联机构的空间运动控制问题进行研究.首先,基于拉格朗日方程建立系统的空间运动数学模型.为了保证所有绳索在机构的工作空间范围内始终处于张紧状态,绳索内力原则被应用于所提的控制方法中.然后,基于李雅普诺夫稳定性理论,给出闭环系统的稳定性证明.最后,为了检验所提控制策略的正确性,给出仿真和实验结果.仿真和实验结果的近似一致性证明了所提控制策略的有效性和合理性.     

机器人轨迹跟踪滑模控制研究

针对多自由度机器人轨迹跟踪问题.设计了一种基于逆向动力学补偿的多输入多输出、降抖振滑模控制策略,给出该控制律的稳定性分析.仿真实验结果表明与鲁棒控制方法相比,控制效果明显得到改善;跟踪误差能在短时间内收敛到0,具有很好的抗干扰性能,并有效降低了抖振.     

PD型模糊学习控制及其在可重复轨迹跟踪问题中的应用

针对可重复轨迹跟踪问题,提出了一种PD型模糊学习算法.该算法集成两种控制:作为基础的PD型模糊逻辑算法和改善系统性能的学习算法.模糊学习控制在模糊控制基础上引入迭代学习算法,使得模糊PD控制器可以精确地跟踪可重复轨迹以及消除周期性扰动.本文在能量函数和泛函分析的基础上,通过严格的推导表明PD型模糊学习算法可达到:1)系统跟踪误差一致收敛到零;2)学习控制序列几乎处处收敛到理想的控制信号.     

机器人系统全局渐近稳定非线性PD+轨迹跟踪控制

采用一类具有“小误差放大、大误差饱和”功能的非线性饱和函数来改进常用的线性比例微分加（ＰＤ＋）机器人系统动力学控制,以形成非线性ＰＤ＋（ＮＰＤ＋）控制,从而获得更快的响应速度和轨迹跟踪精度．应用Ｌｙａｐｕｎｏｖ直接稳定性理论和ＬａＳａｌｌｅ不变性原理证明了闭环系统的全局渐近稳定性．两自由度机器人系统数值仿真结果表明了所提出的ＮＰＤ＋控制具有良好的控制品质．     

基于神经网络的机器人轨迹跟踪控制

针对机器人模型未知情况，讨论了用神经网络和反馈控制实现机械手的跟踪控制。提出一种基于参考误差的投影算法来训练网络权值，训练后网络输出能逼近期望的前馈力矩，并从理论上证明跟踪误差的收敛性。仿真结果表明方案具有较好的跟踪性能和较强的抗干扰能力。     

高精度轨迹跟踪的6-PRRS并联机器人自抗扰控制研究

针对6-PRRS并联机器人控制系统的非线性、耦合等特性,采用分散控制策略。在关节空间设计强鲁棒性的自抗扰控制器对其进行控制．该自抗扰控制器由非线性跟踪微分器、扩张状态观测器、非线性PD和扰动补偿4部分组成．具有模型补偿功能的扩张状态观测器可以获得系统的状态估计和未知外扰的实时作用量,使系统性能得到有效补偿．该控制器以离散的形式进行设计,易于工程实现．仿真结果证明了所提出的控制策略具有强鲁棒性,跟踪性能良好．     

机器人滑模轨迹跟踪控制研究

传统的机器人滑模控制通常采用线性PD滑模和等速趋近率．本文基于指数趋近率并 采用PD+PID滑模策略进行机器人轨迹跟踪控制,即首先采用PD滑模,在达到该滑模后,再采 用PID滑模,取得了很好的效果,文章还对各种饱和函数减少抖振的效果进行了比较．     

PD with sliding mode control for trajectory tracking of robotic system

Good tracking performance is very important for trajectory tracking control of robotic systems. In this paper, a new model-free control law, called PD with sliding mode control law or PD–SMC in short, is proposed for trajectory tracking control of multi-degree-of-freedom linear translational robotic systems. The new control law takes the advantages of the simplicity and easy design of PD control and the robustness of SMC to model uncertainty and parameter fluctuation, and avoid the requirements for known knowledge of the system dynamics associated with SMC. The proposed control has the features of linear control provided by PD control and nonlinear control contributed by SMC. In the proposed PD–SMC, PD control is used to stabilize the controlled system, while SMC is used to compensate the disturbance and uncertainty and reduce tracking errors dramatically. The stability analysis is conducted for the proposed PD–SMC law, and some guidelines for the selection of control parameters for PD–SMC are provided. Simulation results prove the effectiveness and robustness of the proposed PD–SMC. It is also shown that PD–SMC can achieve very good tracking performances compared to PD control under the uncertainties and varying load conditions.     

Model-independent position domain sliding mode control for contour tracking of robotic manipulator

In this paper, a new position domain feedback type sliding mode control (PDC-SMC) law is proposed for contour tracking control of multi-DOF (degree of freedom) nonlinear robotic manipulators focusing on the improvement of contour tracking performances. One feature of the proposed control law is its model-independent control scheme that can avoid calculation of the feedforward part in a standard SMC. The new control law takes the advantages of the high contour tracking performance of PD type feedback position domain control (PDC) and the robustness of SMC. Stability analysis is performed using the Lyapunov stability theory, and simulation studies are conducted to verify the effectiveness of the developed PDC-SMC control system. In addition, the effects of control parameters of the SMC on system performances are studied.     

Disturbance observer-based fixed-time prescribed performance tracking control for robotic manipulator

ABSTRACT

This paper investigates the fixed-time prescribed performance tracking control for the n-DOF uncertain manipulator. First, a novel Barrier Lyapunov Function (BLF) is proposed to guarantee the prescribed performance for the manipulator tracking error. Then, we introduce a disturbance observer to estimate the system uncertainty and disturbance accurately in a predefined time. Next, a composite controller based on the nonsingular fast integral terminal sliding mode is constructed. It is strictly proved that the closed-loop system is stable in fixed-time, which is independent of the initial conditions. Moreover, both transient and steady-state performances of the outputs can be preserved. Finally, numerical simulations and experimental studies are presented to demonstrate the effectiveness of the proposed methods.     

基于自适应动态规划的移动装弹机械臂轨迹控制

针对移动装弹机械臂系统非线性、强耦合、受多种不确定因素影响的问题,本文基于自适应动态规划方法,提出了仅包含评价网络结构的轨迹跟踪控制方法,有效减小了系统跟踪误差.首先,考虑到系统非线性特性、变量间强耦合作用及重力因素的影响,通过拉格朗日方程建立了移动装弹机械臂的动力学模型.其次,针对系统存在不确定性上界未知的问题,建立...     

Guaranteed performance in semi global trajectory tracking for matched disturbance nonlinear systems

In this article, we present a semi global trajectory tracking approach that guarantees a priori computable L ₂ and L _∞ performance bounds for matched disturbance control affine systems. The proposed controller is derived by combining a standard inverse control technique with an extended nonlinear robust state feedback. The latter is based on a control Lyapunov function used for stabilising one operating point inside the considered state space. A difference gradient formulation of this Lyapunov function is then applied to prove stabilisation along any trajectory in the considered state space. Results for L ₂ and L _∞ bounded disturbances will be presented and further extended to the case of actuator uncertainties and disturbance offsets. The theoretical contributions are verified applying them to a numerical example.     

Enhanced feedforward control of non-minimum phase systems for tracking predefined trajectory

This article proposes a novel feedforward controller for non-minimum phase systems by utilising the preview information of the desired trajectory. The performance of the proposed controller is analysed theoretically and verified through the simulation, including comparison with the optimal zero phase error tracking controller and the preview-based stable inversion. The simulation results show that the proposed controller can gain outstanding performance even if the preview time of the desired trajectory is limited.     

Vibration control for a nonlinear three-dimensional flexible manipulator trajectory tracking

This paper proposes an innovative approach to the trajectory tracking in three-dimensional space and vibration control problems in the presence of a nonlinear three-dimensional flexible manipulator based on the partial differential equation model. Unlike two-dimensional plane, we select spherical coordinates to describe the position of the end point in three-dimensional space. This novel approach makes it possible to realise the trajectory tracking by controlling the two angles in spherical coordinates, meanwhile, a vibration control scheme is proposed to restrain vibrations. In addition, the existence and uniqueness of solutions are demonstrated. Finally, the performance of the desired trajectory tracking, the proposed vibration control scheme and their convergence properties are demonstrated by numerical simulations.     

基于函数滑模控制器的机械手轨迹跟踪控制

提出一种基于函数滑模控制器(FSMC)的控制策略,用于不确定机械手的轨迹跟踪控制。首先,由动力学模型和滑模函数得到系统的不确定项;然后,利用RBF神经网络逼近系统不确定项,由于神经网络逼近存在误差,而且在初始阶段误差较大,设计函数滑模控制器和鲁棒补偿项对神经网络逼近误差进行补偿,以克服普通滑模控制器容易引起的抖振问题,同时提高系统的跟踪控制性能。基于李亚普诺夫理论证明了闭环系统的全局稳定性,仿真实验也验证了方法的有效性。     

基于不确定逼近的机械手自适应鲁棒预测控制

针对具有参数不确定性和未知外部干扰的机械手轨迹跟踪问题提出了一种多输入多输出自适应鲁棒预测控制方法. 首先根据机械手模型设计非线性鲁棒预测控制律, 并在控制律中引入监督控制项; 然后利用函数逼近的方法逼近控制律中因模型不确定性以及外部干扰引起的未知项. 理论证明了所设计的控制律能够使机械手无静差跟踪期望的关节角轨迹. 仿真验证了本文设计方法的有效性.