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.     

机械臂轨迹跟踪控制--基于EC-RBF神经网络的机械臂模型参考自适应控制

针对机械臂运动轨迹控制中存在的跟踪精度不高的问题,采用了一种基于EC-RBF神经网络的模型参考自适应控制方案对机械臂进行模型辨识与轨迹跟踪控制。该方案采用了两个RBF神经网络,运用EC-RBF学习算法,采用离线与在线相结合的方法来训练神经网络,一个用来实现对机械臂进行模型辨识,一个用来实现对机械臂轨迹跟踪控制。对二自由度机械臂进行仿真,结果表明,使用该控制方案对机械臂进行轨迹跟踪控制具有较高的控制精度,且因采用EC-RBF学习算法使网络具有更快的训练速度,从而使得控制过程较迅速。     

Robust scheme of global parallel force/position regulators for robot manipulators under environment uncertainty

A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links     

Adaptive tracking control of rigid manipulators using only position measurements

This article presents a new approach to trajectory tracking control of uncertain rigid manipulators using only position measurements. The proposed control strategy is an adaptive scheme that is very general and computationally efficient, requires virtually no information regarding the manipulator dynamic model, and is implementable without calculation of the robot inverse dynamics or inverse kinematic transformations. It is shown that the controller ensures semiglobal uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Additionally, it is demonstrated that the proposed strategy can be used as the basis for developing controllers for “cascaded” robotic systems, such as manipulators with significant actuator dynamics or joint flexibility. The efficacy of this approach to manipulator control is illustrated through both computer simulations and hardware experiments. © 1997 John Wiley & Sons, Inc.     

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.     

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．     

机器人末端臂轨迹跟踪自适应控制设计

本文提出了新颖的机器人末端臂轨迹跟踪自适应控制方法。该方法与已有的神经网络模型不同之处在于数据首先利用运动学反解求出机器人各关节旋转的角度,然后应用径向基函数自组织进行神经网络学习生成模糊规则,利用监督学习算法(SLA)、最小二乘法(LMS)、反向传播算法(BP)和聚类分析的方法在线优化控制规则以及隶属函数的参数。仿真结果表明,该方法不但规则生成的时间少,有效的防止了规则数爆炸,而且在机器人轨迹跟踪控制的应用中效果好。     

Two adaptive control structures of robot manipulators

This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actual trajectory, and an auxiliary input. The second one is the feedforward/feedback control which consists of a feedforward term from the desired position, velocity, and acceleration trajectory based on the inverse of robot dynamics. The feedforward, feedback, and auxiliary gains are adapted using simple equations derived from the decentralized adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the detail parameters of the manipulator or the payload. Simulation results are presented in support of the proposed schemes. The results demonstrate that both controllers perform well with bounded adaptive gains.     

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。     

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.     

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.     

Position and force tracking control of rigid-link electrically-driven robots

This paper introduces a framework for the design of tracking controllers for rigid-link electrically-driven (RLED) robot manipulators operating under constrained and unconstrained conditions. We present an intuitive nonlinear control strategy that can easily be reformulated for robots performing high precision tasks. The main emphasis is placed on the development of controllers that incorporate both motion in freespace and under constrained conditions. Another novelty is the combined treatment of force control and compensation for actuator dynamics. Based on models of the robot dynamics and environmental constraints, a reduced order dynamic model is obtained for the mechanical subsystem with respect to a set of constraint variables. A design procedure for tracking controllers is then formulated for the reduced order manipulator dynamics and the DC actuator dynamics. This paper concentrates on the theoretical aspects of the problem and, hence, is based on exact knowledge of the entire system. However, we have illustrated recently in [1] that this assumption can be generously relaxed in the design of a robust controller following a similar procedure as discussed in this paper.     

Transputer-based implementation of realtime robot position control

The implementation of the forward kinematics algorithm to position control robot manipulators is discussed. The objective is to control the manipulator in real time by dividing the task between a network of transputers. The underlying strategy is the fine-grain distribution of tasks as opposed to allocating one processor per joint. The network topology used is taken through diagnostic tests for analysis leading to performance maximization.     

Visual servoing tracking control of uncalibrated manipulators with a moving feature point

The paper is concerned with the problem of uncalibrated visual servoing robots tracking a dynamic feature point along with the desired trajectory. A nonlinear observer and a nonlinear controller are proposed, which allow the considered uncalibrated visual servoing robotic system to fulfil the desired tracking task. Based on this novel control method, a dynamic feature point with unknown motion parameters can be tracked effectively along with the desired trajectory, even with multiple uncertainties existing in the camera, the kinematics and the manipulator dynamics. By the Lyapunov theory, asymptotic convergence of the image errors to zero with the proposed control scheme is rigorously proven. Simulations have been conducted to verify the performance of the proposed control scheme. The results demonstrated good convergence of the image errors.     

On trajectory and force tracking control of constrained mobile manipulators with parameter uncertainty

This paper studies the trajectory and force tracking control problem of mobile manipulators subject to holonomic and nonholonomic constraints with unknown inertia parameters. Adaptive controllers are proposed based on a suitable reduced dynamic model, the defined reference signals and the mixed tracking errors. The proposed controllers not only ensure the entire state of the system to asymptotically converge to the desired trajectory but also ensure the constraint force to asymptotically converge to the desired force. A detailed numerical example is presented to illustrate the developed methods.     

串联机器人轨迹跟踪控制模糊自适应PID算法的误差修正

提出了一种基于改进PID控制算法的串联机器人轨迹跟踪控制策略,首先采用减聚类的方法和改进的Logistic映射对RBF神经网络进行聚类中心的优化,然后将改进RBF神经网络中的自适应学习机制和自调整能力应用于传统PID控制算法中,对PID控制算法进行最优PID控制参数的选取。仿真实验表明,提出的串联机器人轨迹跟踪控制策略相比较传统PID控制算法,其误差更小,精度更高。     

神经网络自适应滑模控制的不确定机器人轨迹跟踪控制

提出一种针对机器人跟踪控制的神经网络自适应滑模控制策略。该控制方案将神经网络的非线性映射能力与滑模变结构和自适应控制相结合。对于机器人中不确定项,通过RBF网络分别进行自适应补偿,并通过滑模变结构控制器和自适应控制器消除逼近误差。同时基于Lyapunov理论保证机器手轨迹跟踪误差渐进收敛于零。仿真结果表明了该方法的优越性和有效性。     

Force/position tracking for a robotic manipulator in compliant contact with a surface using neuro-adaptive control

The problem of force/position tracking for a robotic manipulator in compliant contact with a surface under non-parametric uncertainties is considered. In particular, structural uncertainties are assumed to characterize the compliance and surface friction models, as well as the robot dynamic model. A novel neuro-adaptive controller is proposed, that exploits the approximation capabilities of the linear in the weights neural networks, guaranteeing the uniform ultimate boundedness of force and position error with respect to arbitrarily small sets, plus the boundedness of all signals in the closed loop. Simulations highlight the approach.     

Sliding mode control for trajectory tracking of mobile robot in the RFID sensor space

This paper presents a sliding mode control method for wheeled mobile robots. Because of the nonlinear and nonholonomic properties, it is difficult to establish an appropriate model of the mobile robot system for trajectory tracking. A robust control law which is called sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. The posture of the mobile robot (including the position and heading direction) is presented and the kinematics equations are established in the two-dimensional coordinates. According to the kinematics equations, the controller is designed to find an acceptable control law so that the tracking error will approximate 0 as the time approaches infinity with an initial error. The RFID sensor space is used to estimate the real posture of the mobile robot. Simulation and experiment demonstrate the efficacy of the proposed system for robust tracking of mobile robots. Recommended by Sooyong Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering (KOSEF) grant funded by the Korea government (MOST) (No. R01-2007-000-10171-0). Jun Ho Lee received the M.S degree in Mechanical Engineering from Pusan National University. His research interests include factory automation and sliding mode control. Cong Lin received the B.S. degree in Electrical Engineering from Jilin University and the M.S degree in Electrical Engineering from Pusan National University. His research interests include neural network and sliding mode control. Hoon Lim is currently a M.S student in Electrical Engineering of Pusan National University. His research interests include mobile manipulator and sliding mode control. Jang Myung Lee received the B.S. and M.S degrees in Electronics Engineering from Seoul National University, Korea. He received the Ph.D. degree in Computer from the University of Southern California, Los Angeles. Now, he is a Professor in Pusan National University. His research interests include integrated manufacturing systems and intelligent control.     

On rotations and translations with application to robot manipulators

Robot motion is described by a set of positions and orientations of the robot's end-effector relative to some base coordinate system. Different methods to describe this motion are available and most of them are presented in this paper. Methods for position vector, free vector, and line vector transformation are presented and compared, and the advantages and disadvantages, the simplicity, and the number of arithmetic operations required of the different methods are addressed. An example of the application of these methods to a six degree-of-freedom robot is given.