Adaptive control based on explicit model of robot manipulator

Adaptive and nonadaptive control algorithms, which make use of a fundamental mathematical property concerning positive definite matrices and Lyapunov stability theory, are proposed for the control of robot manipulators. Using the fact that the matrix dD(q)/dt-2C(q, dq/ dt) is skew symmetric, nonadaptive controllers which have a simplified structure with less computational burden are proposed. Using the dynamic equations for robot manipulators, parameter adaptation rules are developed for updating the controller's partially or totally unknown parameters, generalizing them to model reference adaptive controllers. To further take advantage of the simplified structure of the proposed adaptive controllers, a method for deriving the dynamic model of a robot manipulator which is linear in terms of its parameters is given. This dynamic model is also suitable for the pure identification of the parameters of links and payload of the manipulator     

A predictive controller based on dynamic matrix control for a non-minimum phase robot manipulator

In this paper a hybrid control strategy is presented based on Dynamic Matrix Control (DMC) and feedback linearization methods for designing a predictive controller of five bar linkage manipulator as a MIMO system (two inputs and two outputs). Analyzing the internal dynamic of robot shows the open loop system is unstable and non-minimum phase, so in order to apply the predictive controller, special modifications are needed. These modifications on non-minimum phase behavior are performed using feedback linearization procedure based on state space realization. The design objective is to track a desirable set point as well as time varying trajectories as a command references with globally asymptotical stabilization. The proposed controller is applied to nonlinear fully coupled model of the typical five bar linkage manipulator with non-minimum phase behavior. Simulation results show that the proposed controller has good efficiency. The step responses of system with and without feedback linearization process illustrated that the mentioned modification for stabilizing is performed properly. After applying the proposed predictive controller, the joint angle of robot tracks the reference input while another input acts as the disturbance and vice versa.     

Comparative study of optimization technique for the global performance indices of the robot manipulator based on an approximate model

This paper presents the procedure and results of the multi-objective design optimization of a seven-degrees-of-freedom (7DOF) robot manipulator for better global performance, which pertains to the Global Conditioning Index (GCI) and the Structural Length Index (SLI). The concepts of, and the calculation techniques for, GCI and SLI are introduced to allow their use as objective functions for optimization. The optimization techniques, which are Sequential Two-point Diagonal Quadratic Approximate Optimization (STDQAO), the Progressive Quadratic Response Surface Method (PQRSM), the micro genetic algorithm (μGA), and the evolutionary algorithm (EA), were explained briefly, and they are being used to optimize the global performance indices of the robot manipulator. Also, the results of the optimization and comparison of the four optimization methods are summarized in tables.     

基于代价函数三角网格模型动态简化的研究

模型简化是解决复杂三维模型存储、传输、实时绘制与硬件处理能力的局限性之间矛盾的主要方法。介绍了三角网格模型简化相关技术和算法。目前基于边折叠的三角网格模型简化算法边折叠计算复杂,没有有效进行动态简化,结合Garland的二次误差度量算法和Hoppe的累进网格算法,提出了基于代价函数的三角网格模型动态简化算法。     

Fuzzy control of robot manipulator with a flexible tool

In some tasks, a rigid robot manipulator handles a long, slender, and flexible tool, which usually has not been equipped with vibration measuring devices. This situation makes a different tool tip position control problem. In this paper, a new method will be presented for simultaneous tip position and vibration suppression control of a flexible tool on a rigid‐link 3‐DOF robot. This approach uses fuzzy logic rule‐based controllers without using any sensors and actuators on the tool or a priori knowledge about the tool. Numerical simulation of robot and tool set has been accomplished and results support the fact that designed fuzzy controllers perform remarkably well in reducing vibrations and precision guidance of robot tool tip for tracking various trajectories. © 2005 Wiley Periodicals, Inc.     

Kinematic and dynamic models of hybrid robot manipulator for propeller grinding

In this article, we develop a hybrid robot manipulator for propeller grinding and derive its kinematic and dynamic models. The manipulator is constructed by combining a parallel mechanism and a serial one to increase high stiffness as well as workspace. Based on geometric constraints, inverse–direct kinematics and Jacobian are derived to be implemented in real time control. The velocity control is used to measure the surface of a propeller blade and the position control is conducted to grind the removal depth. The dynamic model, which is developed by a motor algebra, can compute the forces and moments acting at a passive joint and an active one. ©1999 John Wiley & Sons, Inc.     

机械手臂的多模型预测控制

针对机械手臂的非线性特点,提出了基于隶属度函数的多模型预测控制方法。该方法首先根据机械手臂的特点,选择合适的调度变量,将机械手臂的工作空间划分为若干个工作子空间,在每个子空间内的平衡点处对机械手臂进行线性化处理,得到相应的线性子模型,从而得到机械手臂的多模型表示;其次针对每个线性子模型设计局部预测控制器,使其在相应的子空间内达到控制要求;最后选择梯形隶属度函数与局部预测控制器进行加权求和,获得全局多模型预测控制器,以对机械手臂进行控制。仿真结果表明,当机械手臂的工作条件在大范围内变化时,全局多模型预测控制器的控制性能远优于常规PD控制器,达到了预期的控制目的。     

机械手臂基于神经网络动态补偿的自适应控制

研究了模型具有不确定性的机械手臂的跟踪控制问题.由于模型不确定性的存在,基于精确模型设计的控制律很难达到理想的控制效果.针对这种情况,在基于标称模型设计的控制律的基础上,采用神经网络来补偿模型的不确定性,由于神经网络存在逼近误差,因此在控制器设计时,引入了H_∞ 鲁棒项,使得网络逼近误差达到指定的削弱水平并且跟踪误差渐近收敛到零,仿真结果表明了该方法的有效性.     

Kinematic model and calibration of a robot manipulator

In the next generation of industrial robot systems, the absolute positioning accuracy of a robot manipulator is necessary for the manipulation of robot programming systems based on a CAD model database and for integration with multiple robots and hand-eye systems. This paper identifies sources of absolute positioning error, and discusses methods of creating kinematic models and robot calibration including tool-reference-point measurements. High-precision absolute positioning is a key breakthrough required to implement robot systems that can reliably execute control programs generated by offline programming.     

Generalized joint model for robot manipulator kinematic calibration and compensation

A generalized model that goes beyond the usual assumption of “ideal” joint behavior is proposed. The “real” joint has five ancillary degrees of freedom besides the dominant motion. The resulting manipulator transformation with its greater degree of sophistication is expected to help in calibration and compensation of the various kinematic contributions to robot inaccuracy. The procedure to compute this generalized manipulator transformation is presented. The generalized model also results in manipulator differential relationships and these are discussed.     

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。     

A note on control system model simplification

A computer-oriented procedure for the simplification of control systems models for an algebraic method of systems design is presented. The accuracy and simplicity of the algorithm are illustrated. The proposed procedure greatly enhances the practical usefulness of various algegraic design techniques.     

Adaptive tracking control for robot manipulator

In this study, an adaptive control system is proposed for the tracking control of an n-link robot manipulator to achieve high-precision position control. The presentation of the adaptive control system is divided into three parts: a feedforward controller, a state feedback controller and an uncertainty alleviator. All on-line tuning algorithms in the adaptive control system are derived in the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system whether the uncertainties occur. It has learning ability similar to intelligent control, but with a simpler control framework. Computer simulations of a three-link SCARA robot manipulator verify the validity of the proposed control strategy in the possible presence of uncertainties. The merits of the proposed control scheme are that not only can the stability of the controlled system be guaranteed, but also no constrained conditions and prior knowledge of the controlled plant are required in the design process.     

基于微分几何的蛇形机器人移动与操作统一动力学模型研究

蛇形机器人本体是一种多关节串联机构,可以在各种环境中运动,并且当一端固定时可以实现操作.本文提出一种蛇形机器人移动与操作的统一动力学建模方法,统一蛇形机器人移动状态及操作状态的动力学方程.机器人从移动状态到操作状态的转换意味着机构上的重构,即移动状态无固定基座,而操作状态有固定基座.应用虚设机构法在机构学上统一这两种状态(即构形空间中的嵌入关系),利用指数积公式描述这两种状态的运动学方程.在Riemann流形上建立起蛇形机器人移动和操作的动力学模型,并在对动力学模型中各项计算分析的基础上发现机器人操作动力学方程可直接由移动动力学方程退化得到,同时应用子流形的Gauss公式给出证明.由此在微分几何框架下建立蛇形机器人移动与操作的统一动力学模型.按照几何的观点将蛇形机器人移动与操作动力学模型的统一看作是子流形问题,并赋予几何意义.较单独针对蛇形机器人的一种状态(移动或操作)的动力学模型而言,这种统一的动力学模型能够更深刻地揭示蛇形机器人动力学的特征.     

An analytical C3 continuous tool path corner smoothing algorithm for 6R robot manipulator

Tool path smoothness is important to guarantee good dynamic and tracking performance of robot manipulators. An analytical C³ continuous tool path corner smoothing algorithm is proposed for robot manipulators with 6 rotational (6R) joints. The tool tip position is smoothed directly in the workpiece coordinate system (WCS). The tool orientation is smoothed after transferring the tool orientation matrix as three rotary angles. Micro-splines of the tool tip position and tool orientation are constructed under the constraints of the maximum deviation error tolerances in the WCS. Then the tool orientation and tool tip position are synchronized to the tool tip displacement with C³ continuity by replacing the remaining linear segments using specially constructed B-splines. Control points of the locally inserted micro-splines are all evaluated analytically without any iterative calculations. Simulation and experimental results show that the proposed algorithm satisfies constraints of the preset tool tip position and the tool orientation tolerances. The proposed corner smoothing algorithm achieves smoother and lower jerks than C² continuous corner smoothing algorithm. Experimental results show that the tracking errors associated to the execution of the C³ continuous tool path are up to 10% smaller than C² continuous path errors.     

基于反演设计的机器人自适应动态滑模控制

针对机器人跟踪控制问题,设计了一种新型的动态滑模控制器,采用反演（backstepping）方法设计一种新的切换函数,将不连续项转移到了控制的一阶导数中,得到了输入的平滑性的动态滑模控制律。该控制律能保证轨迹跟踪误差的快速收敛性和参数不确定的鲁棒性,仿真实例验证了该控制算法的有效性。     

基于四叉树的动态多分辨率LOD地形快速简化

四叉树和多分辨率技术是目前表示地形结构和显示地形的最佳方式。在研究以往算法基础上,对基于四叉树的动态多分辨率LOD地形简化方法进行改进,建立了适合分辨率要求的节点评价系统,并提出一种双向裂缝消除方法,经距离阈值限制后分别从缩减和剖分两个相反的方向对产生裂缝的相关节点进行处理,在增强简化效果的同时提高了实时渲染的速度。     

A peg-in-hole robot assembly system based on Gauss mixture model

Using robots to assemble parts has always been a research hotspot, but the traditional analysis model of assembly mainly focuses on establishing the linear equation between the feedback force and the relative position of the peg and hole, which leads to high requirements for the material properties and geometric parameters of the assembly parts. In this paper, a new assembly strategy is proposed that learns skills from manual teaching to carry out the assembly process. A Gauss mixture model and regression is used to fit the teaching data, and then, the compliance control method is applied to conduct assembly when the geometric profile parameters and material elastic parameters of the assembly are inaccurate. Finally, the experiment was implemented under the tolerance is 0.18 mm, and the success rate reaches 100%. These findings verified the effectiveness of the compliance control method.