State observer-based robust control scheme for electrically driven robot manipulators

By using a state observer, a new robust trajectory tracking control scheme is developed in this paper for electrically driven robot manipulators. The role of the observer is to estimate joint angular velocities. The proposed controller does not employ adaptation, but assures robust stability of tracking error between joint angles and desired trajectories. At sacrificing asymptotical stability of the tracking errors, the configuration of the proposed controller becomes very simple, compared with regressor-based adaptive controllers. It is shown in the closed-loop system using the proposed controller that the Euclidian norm of tracking errors arrives at any small closed region with any convergent rate by setting only one design parameter. Especially for the desired trajectories converging to constant ultimate values, it is assured that tracking errors converge to zero.     

Actuators fault diagnosis for robot manipulators with uncertain model

In this paper a fault diagnosis approach for robotic manipulators, subject to faults of the joints driving systems, is developed. A model-based diagnostic observer is adopted to detect, isolate and identify failures. Compensation of unknown dynamics, uncertainties and disturbances is achieved through the adoption of a class of neural interpolators, the support vector machines and trained off-line. Interpolation of unknown faults is performed by adopting an on-line neural interpolator based on radial basis functions, whose weights are adaptively tuned on-line. The effectiveness of the approach is experimentally tested on an industrial robot manipulator.     

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.     

A robust neural controller for underwater robot manipulators

Presents a robust control scheme using a multilayer neural network with the error backpropagation learning algorithm. The multilayer neural network acts as a compensator of the conventional sliding mode controller to improve the control performance when initial assumptions of uncertainty bounds of system parameters are not valid. The proposed controller is applied to control a robot manipulator operating under the sea which has large uncertainties such as the buoyancy, the drag force, wave effects, currents, and the added mass/moment of inertia. Computer simulation results show that the proposed control scheme gives an effective path way to cope with those unexpected large uncertainties.     

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.     

A robust fuzzy logic controller for robot manipulators withuncertainties

Owing to load variation and unmodeled dynamics, a robot manipulator can be classified as a nonlinear dynamic system with structured and unstructured uncertainties. In this paper, the stability and robustness of a class of the fuzzy logic control (FLC) is investigated and a robust FLC is proposed for a robot manipulator with uncertainties. In order to show the performance of the proposed control algorithm, computer simulations are carried out on a simple two-link robot manipulator.     

An adaptive control scheme for robot manipulators

An adaptive control scheme is developed for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload.

The presented control scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighbourhood of the trajectory. Then a new adaptive regulation scheme is devised based on the Lyapunov direct method, which generates the variational control that regulates the perturbation in the vicinity of the desired trajectory.     

A robust fault diagnosis scheme based on signal modal estimation

A novel fault detection/diagnosis technique for linear dynamic systems is proposed. In comparison with existing schemes, the proposed method achieves fault detection/diagnosis using neither observer residuals nor parameter estimation errors; instead, it relies on the estimation of the underlying modal parameters of the system. The estimated modal parameters are compared with pre-calculated characteristic patterns of the system, which are represented as a set of root loci in terms of the physical system parameters. The modal parameter estimation is carried out using a numerically robust least-squares algorithm based on singular value decomposition. A pattern recognition technique employing linear multiprototype distance functions is used to classify the faults according to the variations of physical parameters. The proposed method has been applied to a simulated DC servo system where faults are introduced as abrupt changes in physical system parameters. It is shown that the proposed scheme is capable of diagnosing most of changes in physical system parameters.     

冗余机械臂优化控制新方法

针对五自由度冗余机械臂,提出了一种新的基于伪逆的优化控制方法：利用一个可调权值因子,将最小速度范数方法（加速度层）和最小加速度范数方法进行加权组合,来实现对冗余机械臂的运动控制。该优化方法可以实现关节速度范数和关节加速度范数的同时最小化,而且使得机械臂的关节速度在运动末态时接近零。计算机仿真结果进一步验证了所给出的优化控制方法的可行性和优越性。     

On the robust control of robot manipulators

A simple robust nonlinear control law for n-link robot manipulators is derived using the Lyapunov-based theory of guaranteed stability of uncertain systems. The novelty of this result lies in the fact that the uncertainty bounds needed to derive the control law and to prove uniform ultimate boundedness of the tracking error depend only on the inertial parameters of the robot. In previous results of this type, the uncertainty bounds have depended not only on the inertia parameters but also on the reference trajectory and on the manipulator state vector. The presented result also removes previous assumptions regarding closeness in norm of the computed inertia matrix to the actual inertial matrix. The design used thus provides the simplest such robust design available to date     

A robust MIMO terminal sliding mode control scheme for rigidrobotic manipulators

In this paper, a robust multi-input/multi-output (MIMO) terminal sliding mode control technique is developed for n-link rigid robotic manipulators. It is shown that an MIMO terminal switching plane variable vector is first defined, and the relationship between the terminal switching plane variable vector and system error dynamics is established. By using the MIMO terminal sliding mode technique and a few structural properties of rigid robotic manipulators, a robust controller can then be designed so that the output tracking error can converge to zero in a finite time, and strong robustness with respect to large uncertain dynamics can be guaranteed. It is also shown that the high gain of the terminal sliding mode controllers can be significantly reduced with respect to the one of the linear sliding mode controller where the sampling interval is nonzero     

A fast approach for the robust trajectory planning of redunant robot manipulators

In this article, a fast approach for robust trajectory planning, in the task space, of redundant robot manipulators is presented. The approach is based on combining an original method for obstacle avoidance by the manipulator configuration with the traditional potential field approach for the motion planning of the end-effector. This novel method is based on formulating an inverse kinematics problem under an inexact context. This procedure permits dealing with the avoidance of obstacles with an appropriate and easy to compute null space vector; whereas the avoidance of singularities is attained by the proper pseudoinverse perturbation. Furthermore, it is also shown that this formulation allows one to deal effectively with the local minimum problem frequently associated with the potential field approaches. The computation of the inverse kinematics problem is accomplished by numerically solving a linear system, which includes the vector for obstacle avoidance and a scheme for the proper pseudoinverse perturbation to deal with the singularities and/or the potential function local minima. These properties make the proposed approach suitable for redundant robots operating in real time in a sensor-based environment. The developed algorithm is tested on the simulation of a planar redundant manipulator. From the results obtained it is observed that the proposed approach compares favorably with the other approaches that have recently been proposed. © 1995 John Wiley & Sons, Inc.     

冗余机械臂角偏差消去方案之原理分析

本文利用优化方法及递归神经网络实时求解器消除冗余机器手臂在运动过程中出现的角偏差问题.鉴于机器手臂都存在着关节物理约束,我们的优化方案也因此考虑关节极限和关节速度极限的躲避.更重要的是,本文详细分析了该成功解决关节角偏差问题的二次型性能指标的设计原理.仿真结果证实了该方法的可行性与有效性.     

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.     

A robust control scheme for asymptotic tracking of robot motion

In this paper, a controller structure is developed to provide for asymptotic tracking of robot motion. The design tool is the theory of hyperstability and the analysis has led to a simple and an easy-to-implement robust version of the inverse dynamics. Simulation studies are worked out to demonstrate the controller performance. A comparison with other methods is done to show the merits of the developed scheme vs. other recently developed schemes. The implementation and computational requirements of the control schemes are determined and shown to be within the capabilities of new control hardware.This work was supported by the Kuwait University Research Administration under Grant No. EE063.     

Stability analysis of a robust PD control law for robot manipulators

The purpose of this article is to examine the stability of a robust and decentralized PD control law for robot manipulator control. The control law, which was developed by the authors, has been shown experimentally to be extremely simple to implement and highly accurate for position and force tracking in the presence of robot model uncertainty and payload variation. However, stability analysis has been difficult due to the nonlinearity of robot dynamics and the use of time-delayed measurements of joint torques and joint accelerations in the control law. A rigorous stability analysis is presented in this article using Popov's hyperstability theory. A sufficient condition for global stability is obtained that supports previous theoretical and experimental results. © 1996 John Wiley & Sons, Inc.     

Comments on ‘An adaptive control scheme for robot manipulators’

Based on an extension of the classical linearization method, an adaptive control scheme has recently been proposed by Choi et al. (1986). This control scheme, however, implicitly involves taking the inverse of the matrix [I + G(x(t), u(x(t)))], which complicates the computation. Moreover, since the matrix inversion depend- ing on the system state x(t) does not necessarily exist for all time, the proposed control scheme may lose its effectiveness. In this paper, we present a modified control scheme in which the aforementioned weakness does not appear.     

Logarithmic based robust approach to parametric uncertainty for control of robot manipulators

In this paper, a new robust control law for controlling robot manipulators with parameter uncertainty is presented. A controller is designed based on the Lyapunov function and the control law that guarantees the system stability is derived as a result of analytical solution. Apart from previous studies, uncertainty bound and adaptation gain matrix are determined using the estimation law to control the system properly, and so this estimation law is developed as a logarithmic function depending on robot kinematics inertia parameters and tracking error. An application of the proposed control input to a two‐link robot manipulator is presented and numerical simulations are included. Copyright © 2005 John Wiley & Sons, Ltd.     

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...     

Comments on ‘An adaptive control scheme for robot manipulators’

The structure of the adaptive regulator in a paper by Choi et al. (1986) is simplified by utilizing the positive definiteness of the inertia matrix.