Adaptive output feedback tracking control of robot manipulators using position measurements only

In this paper, a new adaptive neuro controller for trajectory tracking is developed for robot manipulators without velocity measurements, taking into account the actuator constraints. The controller is based on structural knowledge of the dynamics of the robot and measurements of joint positions only. The system uncertainty, which may include payload variation, unknown nonlinearities and torque disturbances is estimated by a Chebyshev neural network (CNN). The adaptive controller represents an amalgamation of a filtering technique to generate pseudo filtered tracking error signals (for the elimination of velocity measurements) and the theory of function approximation using CNN. The proposed controller ensures the local asymptotic stability and the convergence of the position error to zero. The proposed controller is robust not only to structured uncertainty such as payload variation but also to unstructured one such as disturbances. Moreover the computational complexity of the proposed controller is reduced as compared to the multilayered neural network controller. The validity of the control scheme is shown by simulation results of a two-link robot manipulator. Simulation results are also provided to compare the proposed controller with a controller where velocity is estimated by finite difference methods using position measurements only.     

Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

Many robot controllers require not only joint position measurements but also joint velocity measurements; however, most robotic systems are only equipped with joint position measurement devices. In this paper, a new output feedback tracking control approach is developed for the robot manipulators with model uncertainty. The approach suggested herein does not require velocity measurements and employs the adaptive fuzzy logic. The adaptive fuzzy logic allows us to approximate uncertain and nonlinear robot dynamics. Only one fuzzy system is used to implement the observer-controller structure of the output feedback robot system. It is shown in a rigorous manner that all the signals in a closed loop composed of a robot, an observer, and a controller are uniformly ultimately bounded. Finally, computer simulation results on three-link robot manipulators are presented to show the results which indicate good position tracking performance and robustness against payload uncertainty and external disturbances.     

Perfomance-based adaptive tracking control of robot manipulators

This article presents two new adaptive schemes for the motion control of robot manipulators. The proposed controllers are very general and computationally efficient because they do not require knowledge of either the mathematical model or the parameter values of the manipulator dynamics, and are implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategies are globally stable in the presence of bounded disturbances, and that in the absence of disturbances the ultimate bound on the size of the tracking errors can be made arbitrarily small. Computer simulation results are given for a PUMA 560 manipulator, and demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed controllers. Experimental results are presented for an IMI Zebra Zero manipulator and confirm that the control schemes provide a simple and effective means of obtaining high-performance trajectory tracking. © 1995 John Wiley & Sons, Inc.     

Decentralized adaptive tracking control of robot manipulators

An asymptotically stable decentralized adaptive control scheme is presented to enable accurate trajectory tracking without requiring specific knowledge about the robot dynamics. The scheme is based on expressing the robot dynamics as the product of individual joint quantities, and bounds on certain robot parameters. Parameter adaptation laws are derived using the Lyapunov theory, and asymptotic stability of tracking errors, and boundedness of parameter estimates are established. The control system is shown to be robust to torque disturbances affecting the system and to a class of unmodeled dynamics. The structure of the controller and the performance of the closed-loop system are analyzed. Simulations results using the complete dynamic model of a six degree of freedom industrial robot are presented to demonstrate the excellent tracking performance of the proposed adaptive control scheme. © 1996 John Wiley & Sons, Inc.     

机器人系统输出反馈重复学习轨迹跟踪控制

针对高度非线性多关节机器人的轨迹跟踪问题,提出一类输出反馈重复学习控制算法,使得在只有位置信息可测以及模型信息不确定的条件下即能获得良好的控制品质.非线性滤波器的引入解决了现实中速度信号较难获得的问题,重复学习控制策略实现了对周期性参考输入的渐近稳定跟踪.应用Lyapunov直接稳定性理论证明了闭环系统的全局渐近稳定性.三自由度机器人系统数值仿真结果表明了所提出的输出反馈重复学习控制的有效性.     

Finite-time tracking control for robot manipulators with actuator saturation

This paper addresses the finite-time tracking of robot manipulators in the presence of actuator saturation. The commonly-used proportional-derivative (PD) plus dynamics compensation (PD+) scheme is extended by replacing the linear errors in the PD+ scheme with saturated non-smooth but continuous exponential-like ones. Advantages of the proposed controller include semi-global finite-time tracking stability featuring faster transient and high-precision performances and the ability to ensure that actuator constraints are not violated. This is accomplished by selecting control gains a priori, removing the possibility of actuator failure due to excessive torque input levels. Lyapunov's direct method and finite-time stability are employed to prove semi-global finite-time tracking. Simulations performed on a three degree-of-freedom (DOF) manipulator are provided to illustrate the effectiveness and the improved performance of the formulated algorithm.     

On the PID tracking control of robot manipulators

We consider the problem of PID tracking control of robotics manipulators. Our objective is to prove that under classical PID control, semiglobal stability can be assured with arbitrary small output tracking error. This means that, for any given set of initial conditions W_x, there exist PID control gains such that all trajectories starting in W_x converge to a residual set of arbitrary size. A novel PID control configuration is developed in terms of a parameter that is directly related with the size of the region of attraction and the size of the residual set. Tuning guidelines are extracted from the stability analysis.     

Global finite-time inverse tracking control of robot manipulators

This paper addresses the global finite-time tracking of robot manipulators. By replacing with the nonlinear exponential-like errors, the commonly used inverse dynamics control for robot manipulators is modified to produce global finite-time tracking. Using this method, the controlled robotic system is transformed into a nonlinear and decoupled one, and thus the tracking performance is very convenient to quantify. A Lyapunov-like argument along with finite-time stability analysis is employed to prove global finite-time stability. Simulations performed on a two degree-of-freedom (DOF) manipulator are provided to illustrate the effectiveness and the improved performance of the formulated algorithm.     

输入力矩受限的机器人鲁棒自适应跟踪控制

在输入力矩受限的情况下, 提出一种全新的简单鲁棒自适应跟踪控制算法, 当参数的估计范围包含其真实值时, 证明了闭环系统的渐近稳定跟踪;当有干扰存在, 常规参数估计自适应控制算法不能实现稳定控制时, 本算法仍然使系统稳定, 在本算法中, 所估计的参数在跟踪控制律前馈项中表现为非线性, 这是区别于常规参数估计自适应算法的一个最重要特征. 因此本算法控制器的设计更有灵活性, 另一方面获得更好的控制品质和鲁棒性, 特别是对参数域估计误差即参数范围估计错误的强鲁棒性, 均为仿真算例所验证.     

Global trajectory tracking through output feedback for robot manipulators with bounded inputs

In this work, a globally stabilizing output feedback scheme for the trajectory tracking of robot manipulators with bounded inputs is proposed. It achieves the motion control objective avoiding input saturation and excluding velocity measurements. Moreover, it is not defined using a specific sigmoidal function, but any one on a set of saturation functions. Consequently, the proposed scheme actually constitutes a family of globally stabilizing output feedback bounded controllers. Furthermore, the control gains are not tied to satisfy any saturation‐avoidance inequality and may consequently take any positive value, which may be considered beneficial for performance adjustment/improvement purposes. Further, a class of desired trajectories that may be globally tracked avoiding input saturation and excluding velocity measurements is completely characterized. Global asymptotic stabilization of the closed‐loop system solutions towards the pre‐specified desired trajectory is proved through a strict Lyapunov function. The efficiency of the proposed scheme is corroborated through experimental results. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

机器人自适应PID饱和输出反馈控制

针对机器人系统在仅有位置传感、驱动器饱和、存在建模不确定性及干扰等条件下的轨迹跟踪控制问题,提出了一种新的自适应PID控制方案。采用高精度滤波器估计机器人关节速度,采用带饱和函数的控制器限制输出力矩,采用自适应PID控制器补偿建模不确定性和干扰。通过Lyapunov直接法,证明系统的稳定性。最后以两关节机器人为例,给出仿真实验结果,验证了算法的有效性。     

自适应神经变结构的机器人轨迹跟踪控制

提出一种神经网络与变结构融合的控制策略用于非线性机器人控制,该方案利用神经网络来自适应补偿不确定模型,并通过变结构控制器消除逼近误差.考虑到局部泛化网络的不足,根据其状态空间的划分,分别对3个区间采用神经网络与变结构的分级与集成控制.该方案能在控制阶段初期及网络逼近区域外使两种控制器共同起作用以保持系统的强鲁棒性,基于Lyapunov理论证明了闭环系统的全局稳定性.仿真结果进一步表明了该方法的优越性.     

力矩输入有界的柔性关节机器人轨迹跟踪控制

为解决柔性关节机器人在关节驱动力矩输出受限情况下的轨迹跟踪控制问题,提出一种基于奇异摄动理论的有界控制器.首先,利用奇异摄动理论将柔性关节机器人动力学模型解耦成快、慢两个子系统.然后,引入一类平滑饱和函数和径向基函数神经网络非线性逼近手段,依据反步策略设计了针对慢子系统的有界控制器.在快子系统的有界控制器设计中,通过关节弹性力矩跟踪误差的滤波处理加速系统的收敛.同时,在快、慢子系统控制器中均采用模糊逻辑实现控制参数的在线动态自调整.此外,结合李雅普诺夫稳定理论给出了严格的系统稳定性证明.最后,通过仿真对比实验验证了所提出控制方法的有效性和优越性.     

Robust tracking control of nonholonomic dynamic systems with application to the bi-steerable mobile robot

A tracking controller for nonholonomic dynamic systems is proposed which allows global tracking of arbitrary reference trajectories and renders the closed loop system robust with respect to bounded disturbances. The controller is based on [Chwa, D. (2004). Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates. IEEE Transactions on Control Systems Technology, 12(4), 637-644] and shows several generalizations and improvements. The control law for tracking of general nonholonomic systems using inverse kinematic models (IKM) and sliding surfaces is stated. Conditions are proven under which robust tracking is achieved for a specific system. Tracking control is applied to the bi-steerable mobile robot, and simulation results are presented.     

Switched adaptive tracking control of robot manipulators with friction and changing loads

A switched adaptive controller is designed for robot manipulators with friction and changing loads. The nonlinear friction is depicted by a nonlinear friction model, and a switched nonlinear system is used to model the parameter jump caused by load change. Hyperstability theory is used in the designing procedure, which provides more options for adaptive laws than Lyapunov theory. In the presence of friction and changing loads, asymptotic tracking is achieved under arbitrary switching, which is not able to accomplish by a non-switched adaptive controller. The proposed method is validated by a simulation of a 2 degree of freedom manipulator.     

Tracking control via switched Integral Sliding Mode with application to robot manipulators

This paper presents a switching structure scheme for motion control of industrial robot manipulators. To overcome the issues deriving from choosing a priori a specific control scheme, which can result in limited performances when the operating condition of the system varies, the scheme implements both a decentralized approach, suited for lower performance requirements and high transmission ratios, and the inverse dynamics based centralized approach, suited for higher performances in terms of velocity and acceleration. In both cases, the Integral Sliding Mode algorithm is used to compensate matched disturbances and to estimate the unmodeled dynamics used for the switching decision mechanism.     

Global sliding mode with fractional operators and application to control robot manipulators

In this paper, a novel fractional-order global sliding-mode control scheme is presented. It is first used to stabilise a coupled second-order nonlinear system, and then it is generalised to control a class of multi-input and multi-output nonlinear systems with the model uncertainties and external disturbances. The proposed sliding manifold, which will converge to the origin in finite time by utilising a classical quadratic Lyapunov function, ensures global stabilisation of the system and the reduction of the chattering phenomenon during the control processes. Based on input-to-state stability and Lyapunov's stability theorem, the closed-loop system can be globally uniformly asymptotically stabilised to the origin in the future time. Some results about the control and stabilisation of integer-order nonlinear systems, when the fractional-order sliding-mode controller is used, are illustrated in this paper. Finally, an application to two-degree of freedom polar robot manipulator is provided to show the validity and feasibility of the proposed method.     

Adaptive trajectory tracking neural network control with robust compensator for robot manipulators

Neural Computing and Applications - This paper presents an adaptive trajectory tracking neural network control using radial basis function (RBF) for an n-link robot manipulator with robust...     

机械手的在线鲁棒自适应神经网络跟踪控制

考虑了一类具有外界干扰和不确定性的机械手臂轨迹跟踪鲁棒控制问题. 控制器由自适应RBF(radial basis function)神经网络控制器和PD控制器组成. 采用基于神经元灵敏度和获胜神经元概念的GP–RBF算法, 在线确定神经网络的初始结构和参数. 当误差满足一定要求时, 根据Lyapunov稳定性理论的自适应律进一步调整网络权值, 以保证机械手位置误差和速度跟踪误差渐近收敛于零. 所设计的控制器可保证闭环系统的稳定性和鲁棒性. 仿真结果证明了本文方法的有效性.     

Trajectory tracking control for robot manipulators using only position measurements

In the paper, the trajectory tracking control problem is investigated for robotic manipulators which are not equipped with the tachometers. Our contribution consists in establishing uniform asymptotic stability in closed-loop system by using the dynamic position-feedback controller with feedforward. Using Lyapunov vector function and comparison principle, we construct the non-linear controller with variable gain matrices and first-order linear dynamic compensator such that the origin of the closed-loop system is uniformly asymptotically stable. The controller is shown to be robust with respect to parameters incertainties. We illustrate the utility of our result by simulation tests with reference to a two-link planar elbow robot manipulator.