滑动及侧滑影响下的移动机器人轨迹跟踪控制

对受滑动及侧滑影响的移动机器人轨迹跟踪控制问题进行研究。在动力学部分,通过模糊系统逼近系统中的未知非线性,H_∞控制对滑动和侧滑干扰因素的补偿,利用Lyapunov函数推导出模糊参数的自适应律,设计出基于动力学的自适应模糊控制器。在运动学部分,设计逆运动学控制器,处理移动机器人实际位置与期望位置的误差,得到移动机器人运动的期望速度。将逆运动学控制器与自适应模糊控制器级联,并通过Lyapunov方法证明控制系统的稳定性。与自适应动力学控制器进行比较。仿真结果表明:在滑动及侧滑的影响下提出的策略具有较好的轨迹跟踪性能。     

具有未校准视觉参数的移动机器人的跟踪控制

基于未校准视觉反馈的非完整运动学系统具有参数不确定性,较一般的运动学系统更加复杂.根据视觉反馈和非完整移动机器人的链式标准形式,研究了具有未标定摄像机视觉参数的移动机器人的轨迹跟踪控制问题.利用固定在天花板上的摄像机系统提出运动学跟踪误差模型,并对该误差系统模型提出了一种动态反馈跟踪控制器;对具有不确定机械参数的动力学模型,提出一种自适应力矩控制器,该控制器保证了实际机器人状态渐近跟踪给定的参考轨迹,并通过Lyapunov方法严格证明了整个闭环系统的稳定性.仿真结果证实了所提出的控制器的有效性.     

考虑参数不确定性的移动机器人轨迹跟踪控制

针对移动机器人系统中轮胎半径和轮胎间距存在的参数不确定性问题,提出自适应轨迹跟踪控制方法.首先,推导适合进行自适应控制器设计的系统误差模型,将原有控制问题转化为不确定参数的自适应更新率和虚拟控制输入的设计问题;然后,针对系统中的不确定性参数,设计自适应更新率对其进行在线估计,并设计虚拟的控制输入,得到移动机器人驱动电机的左右轮转速;其次在Lyapunov稳定性框架下证明闭环跟踪误差系统的渐近稳定性和估计误差系统的稳定性;最后通过仿真和实验表明,所提出方法能够通过在线学习估计出参数真实值,使得实际运行轨迹收敛到参考轨迹,同时表明所提出方法能够抑制系统参数不确定性对控制系统的影响.     

音圈电机伺服系统的自适应非光滑控制

针对音圈电机伺服系统的轨迹跟踪控制品质受动力学参数不确定性及外部扰动影响的问题,建立动力学模型,结合自适应控制与非光滑控制理论,设计一种自适应非光滑控制方法,并理论证明了闭环系统的渐近稳定性．最后,通过仿真实验及其对比来验证所设计方法的有效性,仿真结果表明,所设计方法具有自适应控制的补偿能力与非光滑控制的快速收敛特性,能够克服不确定性影响,有效提高音圈电机伺服系统的轨迹跟踪控制品质．     

多电机驱动系统的保性能鲁棒Funnel控制

本文针对含参数不确定性的多电机驱动系统,提出一种基于最优保性能鲁棒的Funnel控制方法实现系统的规定跟踪性能.该控制方法通过构造Funnel函数对误差系统进行变换,并设计自适应反步控制器保证变换后系统的稳定性即可使跟踪误差的瞬态和稳态响应均被限制在给定的Funnel边界内.然而由于系统中存在的参数不确定性会影响系统的规定控制性能,本文在Funnel控制基础上又设计了最优保性能鲁棒控制器.它是通过将参数不确定性系统的保性能鲁棒控制问题转化为标称系统的最优控制问题,并求解新的黎卡提方程而得到的.因此所设计的控制器不但消除了参数不确定性对系统的影响并且能够使系统的性能指标达到一确定的上界.最后,对四电机驱动系统进行了仿真和实验验证,说明所提出控制方法的有效性.     

基于视觉的AGV轨迹跟踪控制

以物流搬运自动导向车AGV的轨迹跟踪为研究目标.对三轮式AGV的运动特性进行了分析,分别建立了AGV在任务空间和视觉空间内的运动学模型.根据针孔摄像机的成像原理,实现了AGV速度矢量由任务空间到视觉空间的映射.采用视觉伺服控制方法,获得了AGV轨迹跟踪的控制规律,并利用Lyapunov函数验证了控制系统的渐近稳定性.以具有任意初始误差的圆和直线为参考轨迹,对控制系统进行了仿真研究.仿真结果表明了控制策略的有效性和正确性.     

任务空间内空间机器人的鲁棒复合自适应控制

对于本体姿态受控而位置不受控的空间机器人系统,其任务空间内自适应控制的难点在于系统的Jacobian矩阵与系统的动力学参数有关,因此当系统存在参数有确定性时,无法通过运动学关系式将任务空间轨迹精确地转换为关节空间轨迹。为解决任务空间内的轨迹跟踪操和任务,本文提出了一种鲁棒复合适应控制方法,证明了当系统存在参数不确定性及非参数不确定性（包括扰动、未建模动态）时,这种方法可以保证系统全局一致最终有界。仿真结果验证了算法的有效性。     

含未标定摄像机参数的非完整移动机器人的自适应动力学跟踪控制

结合一类非完整移动机器人的运动学模型和链式转换,在质心与几何中心重合的情况下,研究含有未知参量的非完整移动机器人的跟踪控制问题.首先,利用针孔摄像机模型提出一种基于视觉伺服的运动学跟踪误差模型;然后在此模型下,将动态反馈、Back-stepping技巧与自适应控制相结合,设计一个区别于以往处理方法、含有两个动态反馈的自适应跟踪控制器,从而实现动力学系统的全局渐近轨迹跟踪,并通过李亚普诺夫方法严格证明闭环系统的稳定性和估计参数的有界性;最后,利用Matlab仿真验证所提出的控制器的有效性.     

非完整移动机器人轨迹跟踪自适应控制器设计

针对轮式移动机器人的非完整运动学模型,将自适应反演控制技术和李亚普诺夫稳定性理论应用于机器人轨迹跟踪控制,设计了具有全局渐近稳定性的自适应轨迹跟踪控制器,并在Matlab环境下实现了移动机器人对直线和椭圆2种轨迹追踪的仿真实验.实验表明:该控制方法在轨迹跟踪控制中有较好的航向跟踪效果,对机器人非完整系统模型的非线性特性...     

基于RBF神经网络的作业型AUV自适应终端滑模控制方法及实验研究

研究了作业型AUV （自主水下机器人）的轨迹跟踪控制问题.实际作业中,水下机械手展开作业过程将引起AUV动力学性能变化,进而影响AUV轨迹跟踪控制;并且水流环境干扰亦将影响AUV轨迹跟踪控制.针对上述AUV轨迹跟踪控制问题,提出一种基于RBF （径向基函数）神经网络的AUV自适应终端滑模运动控制方法.该方法在李亚普诺夫稳定性理论框架下,采用RBF网络对机械手展开引起的AUV动力学性能变化和水流环境干扰进行在线逼近,并结合自适应终端滑模控制器对神经网络权值和AUV控制参数进行自适应在线调节.通过李亚普诺夫稳定性理论,证明AUV系统轨迹跟踪误差一致稳定有界.针对滑模控制项引起的控制量抖振问题,提出一种变滑模增益的饱和连续函数滑模抖振降低方法,以降低滑模控制量抖振.通过AUV实验样机的艏向和垂向的轨迹跟踪实验,验证了本文AUV系统控制方法和滑模降抖振方法的有效性.     

Task-space fully distributed tracking control of networked uncertain robotic manipulators without velocity measurements

This paper investigates the task-space synchronised tracking problem of uncertain networked manipulators interconnected on directed graphs, where the dynamic leader is available to only a subset of followers and followers have only local interaction. A fully distributed tracking controller is proposed, which is composed of a distributed desired trajectory estimator, a joint-space velocity observer and an adaptive cooperative control algorithm. Specifically, the proposed controller allows each manipulator to track the dynamic leader solely using local task-space position measurements. Besides, in the presence of both dynamic and kinematic uncertainties, the adaptive cooperative control algorithm indeed improves the system's robustness. Furthermore, it is strictly proved that the proposed control scheme ensures that both task-space position and velocity tracking errors converge to zero as time tends to infinity. In the end, simulation results are provided to demonstrate the effectiveness of the proposed controller.     

Saturated Adaptive Output-Constrained Control of Cooperative Spacecraft Rendezvous and Docking

This paper investigates the robust relative pose control for spacecraft rendezvous and docking with constrained relative pose and saturated control inputs. A barrier Lyapunov function is used to ensure the constraints of states, so that the computational singularity of the inverse matrix in control command can be avoided, while a linear auxiliary system is introduced to handle with the adverse effect of actuator saturation. The tuning rules for designing parameters in control command and auxiliary system are derived based on the stability analysis of the closed-loop system. It is proved that all closed-loop signals always keep bounded, the prescribed constraints of relative pose tracking errors are never violated, and the pose tracking errors ultimately converge to small neighborhoods of zero. Simulation experiments validate the performance of the proposed robust saturated control strategy.      

Adaptive inverse dynamics control of robots with uncertain kinematics and dynamics

It has been about two decades since the first globally convergent adaptive tracking controller was derived for robots with dynamic uncertainties. However, not until recently has the problem of concurrent adaptation to both the kinematic and dynamic uncertainties found its solution. This adaptive controller belongs to passivity-based control. Though passivity-based controllers have many attractive properties, in general, they are not able to guarantee the uniform performance of the robot over the entire workspace. Even in the ideal case of perfect knowledge of the manipulator parameters, the closed-loop system remains nonlinear and coupled. Thus the closed-loop tracking performance is difficult to quantify, while the inverse dynamics controllers can overcome these deficiencies. Therefore, in this work, we will develop a new adaptive Jacobian tracking controller based on the inverse manipulator dynamics. Using the Lyapunov approach, we have proved that the end-effector motion tracking errors converge asymptotically to zero. Simulation results are presented to show the performance of the proposed controller.     

不确定非完整移动机器人的轨迹跟踪控制

具有未校准视觉参数的非完整移动机器人的运动学系统具有参数不确定性,较一般的运动学系统更加复杂.基于视觉反馈、Barbalat's定理和Lyapunov直接方法,研究了具有未标定摄像机参数的非完整移动机器人的轨迹跟踪问题.首先,利用固定在天花板上的针孔摄像机透视投影模型,提出了一种新的基于视觉伺服的移动机器人运动学跟踪误差模型;基于这个模型,提出了一种新的与未知视觉参数无关的动态反馈跟踪控制器.该控制器不仅保证系统的状态渐近跟踪给定参考轨迹,而且控制器是全局的,通过Lyapunov方法严格证明了闭环系统的稳定性.在惯性系和图像坐标系下讨论跟踪问题,使问题变的简单且设计的控制器更加有用.最后,仿真结果证实了所提出的控制器的有效性.     

Neural-network control of mobile manipulators

In this paper, a neural network (NN)-based methodology is developed for the motion control of mobile manipulators subject to kinematic constraints. The dynamics of the mobile manipulator is assumed to be completely unknown, and is identified online by the NN estimators. No preliminary learning stage of NN weights is required. The controller is capable of disturbance-rejection in the presence of unmodeled bounded disturbances. The tracking stability of the closed-loop system, the convergence of the NN weight-updating process and boundedness of NN weight estimation errors are all guaranteed. Experimental tests on a 4-DOF manipulator arm illustrate that the proposed controller significantly improves the performance in comparison with conventional robust control.     

Robust adaptive control for a nonholonomic mobile robot with unknown parameters

A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.     

基于逼近误差调节的直接自适应模糊控制

对含未知参数的一类非线性系统给出一种新的直接自适应模糊控制方案．利用在线自适应调节估计逼近误差,用此估计值设计补偿器减小逼近误差对跟踪精度的影响．该方法不仅能够保证闭环系统的稳定性,而且可以使跟踪误差收敛到0或0的小邻域．     

电流型脉宽调制在异步电动机转速控制中的应用

针对电压型PWM存在的缺点,提出一种电流型脉宽调制方法,并在此基础上对异步电动机的转速控制系统进行分析．仿真结果表明,这是一种电流跟随控制系统,其动静态特性好,转速闭环系统稳定性高,调速范围宽,最低转速可以为零．它允许对系统的所有参数包括速度调节器参数进行变动。     

Trajectory tracking control of mobile robots without using longitudinal velocity measurements

We propose a new robust trajectory tracking control scheme for wheeled mobile robots without longitudinal velocity measurements. In the proposed controller, a velocity observer is used to estimate the longitudinal velocity of a wheeled mobile robot. A wheeled mobile robot model, including motor dynamics, is used to develop the controller. The developed controller has the following useful properties. (1) The developed controller does not require any accurate knowledge of the robot parameters or the motor parameters. Even if there are uncertainties in the robot dynamics, including the motor properties, it is certain that tracking errors ultimately become uniformly bounded in a closed-loop system using the developed controller. (2) It is shown theoretically that the ultimate norms of tracking errors can easily be reduced by setting only one design parameter.     

On trajectory tracking control for nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances

This paper studies the trajectory tracking control problem of mobile manipulators subject to nonholonomic constraints, operating in task space, with the presence of external torque disturbances and dynamic uncertainties. The proposed controls are robust to external torque disturbances and can overcome the effects of the unknown dynamic parameters. The stability of the closed-loop system and the asymptotic convergences of tracking errors are proved using Lyapunov synthesis. The proposed control strategies have been designed to drive the system motion converges to the desired manifold and, at the same time, guarantees the boundedness of all the closed-loop signals. Simulation results validate that the system trajectory converge to the desired one.