一类不确定非完整移动机械臂的鲁棒镇定

讨论了一类带有未知惯性参数,未建模动态及外界干扰的非完整动力学系统的鲁棒镇定问题．基于滑模控制思想及非完整运动学系统的镇定策略,给出了该类系统的鲁棒镇定方法．将其用于一类不确定非完整移动机械臂的鲁棒镇定分析,仿真结果验证了所提出控制方法的正确有效性．     

基于自适应动态规划的移动装弹机械臂轨迹控制

针对移动装弹机械臂系统非线性、强耦合、受多种不确定因素影响的问题,本文基于自适应动态规划方法,提出了仅包含评价网络结构的轨迹跟踪控制方法,有效减小了系统跟踪误差.首先,考虑到系统非线性特性、变量间强耦合作用及重力因素的影响,通过拉格朗日方程建立了移动装弹机械臂的动力学模型.其次,针对系统存在不确定性上界未知的问题,建立...     

基于参数不确定机械臂系统的自适应轨迹跟踪控制

针对机械臂系统惯性参数及运动学参数不能准确测量进而影响轨迹跟踪性能的问题,提出一种任务空间自适应轨迹跟踪控制方法,通过定义关节角速度参考误差,并将任务空间的轨迹跟踪误差及运动学参数误差反馈给控制器,以改善系统稳定性,设计电机参数传输矩阵及电机参数自适应率,以抵消电机发热引起参数漂移对跟踪性能影响,并给出了稳定性证明.实验结果表明,该方法能够较好地克服电机参数漂移对跟踪控制性能的影响.     

非完整移动机械臂的避障运动规划

针对有空间障碍物避免的移动式操作机器人系统运动规划问题，提出了一种基于特殊的人工势函数，使用局部距离信息实现非完整移动机械臂系统实时避障运动规划方法，并且用Lyapunov定理证明了闲环系统的稳定性。用提出的方法对非完整移动机械臂系统进行仿真．仿真结果表明了它的正确有效性。     

不确定非完整动力学系统的时变自适应控制

研究了具有未知惯性参数非完整动力学系统的镇定问题,对于一类非完整系统,给出了一种新的时变自适应律镇定律,不同于其它文中的控制律,该镇定律不是高增益的,文中也讨论了一般不确定非完整动力学系统的镇定问题,证明了时变周期镇定律的存在性,一个简单的例子说明了如何应用文中结果设计镇定律,仿真结果表明了本文所提设计方法的有效性。     

基于扰动观测器的机械臂自适应反演滑模控制

机械臂的动力学模型通常包含一定的结构不确定性,并受到外界未知干扰的影响。针对现有模型的不确定性特点,提出了一种基于非线性扰动观测器的自适应反演滑模控制方法,解决机械臂的轨迹跟踪控制问题。对于外界干扰,利用非线性扰动观测器进行观测补偿,无需上界先验知识;对于结构不确定性,引入反演滑模控制,同时设计自适应律,保证闭环系统的稳定性并增强系统的动态适应性。仿真结果证明,所提出的方法可以有效克服系统不确定性,降低控制输入信号的抖振,最终实现期望轨迹的快速精确跟踪。     

非完整移动机械臂的鲁棒跟踪控制

针对非完整移动机械臂惯性参数的不确定性,采用滑模控制为其设计了输出跟踪控制器。首先给出了包括驱动电机动态特性的非完整移动机械臂的简化动态模型,然后通过微分同胚和输入变换将其分解为4个低阶子系统,并给出了其输出跟踪的滑模控制器设计方法。仿真实验表明,所设计的鲁棒控制器能很好地跟踪给定轨迹。     

柔性机械臂运动轨迹的鲁棒自适应控制

本文针对多连杆柔性机械臂的运动轨迹问题，讨论了动力学建模，控制系统结构设计以及鲁棒自适应控制法，运用假设模记方法得到了柔性机械臂动力学所似方程，通过对柔性机械臂动力学特性分析，建立了等价动力学模型，依此提出了一种鲁棒自适应控制算法，并给出仿真研究结果。     

任务空间内空间机械臂的自适应控制

对于本体姿态受控而位置不受控的空间机械臂系统,本文在任务空间内给出了一种自适应控制算。证明了当系统存在参数不确定性时,该算汉不但可以保证末端招待器在任务空间内的位置轨迹跟踪误差渐近收敛,而且还可保证在关节空间的角偏差及角偏差速率渐近收敛。仿真结果验证了算法的有效性。     

轮式移动机械臂的鲁棒跟踪控制研究

移动机械臂系统一般由移动平台和机器臂组成,它既具有机器臂的操作灵活性,又具有移动机器人的可移动性,因此其应用范围要比单个系统宽得多。这篇文章研究了由非完整移动平台和完整机械臂构成的移动机械臂系统的鲁棒跟踪控制问题,基于误差动态方程和耗散不等式引理设计了一种鲁棒跟踪控制器,该控制器在出现外界干扰时能使系统渐近跟踪给定信号。使用Matlab6.5对系统进行了仿真研究,仿真结果表明所提出的鲁棒控制算法是正确有效的。     

加前馈补偿的工业机器人自适应控制

工业机器人的控制是一个复杂的非线性控制问题.本文针对由Lagrange-Euler方程描述的工业机器人动力学模型,提出了两种加前馈补偿的自适应控制方法,并从理论上证明了系统的渐近稳定性. 考虑自由度为n的工业机器人,由Lagrange-Euler方程知其动力学方程为M(q)q+d(q,q)+g(q)=u.(1)其中g∈R~n为广义坐标向量;n∈R~n为广义控制向量;M(·)∈R~(n×n)为惯性矩阵;d(·,·)∈R~n为哥氏力与向心力向量;g(·)∈R~n为重力向量,一般M(·)非奇异. 设与(1)式并联的参考模型为     

Adaptive Motion/Force Tracking Control for a Class of Mobile Manipulators

In this paper, modeling and adaptive motion/force tracking control is considered for a class of mobile manipulators under the holonomic and affine constraints with the presence of uncertainties and disturbances. Based on a suitable reduced dynamic model, adaptive controllers are proposed to ensure that the states of a closed‐loop system asymptotically track desired trajectories while the constraint force remains bounded by tuning design parameters. Detailed simulation results confirm the effectiveness of the control strategy.     

Adaptive Task-Space Control of Flexible-Joint Manipulators

This paper considers the motion control and compliance control problemsfor uncertain rigid-link, flexible-joint manipulators, and presents newadaptive task-space controllers as solutions to these problems. The motioncontrol strategy is simple and computationally efficient, requires littleinformation concerning either the manipulator or actuator/transmissionmodels, and ensures uniform boundedness of all signals and arbitrarilyaccurate task-space trajectory tracking. The proposed compliant motioncontrollers include an adaptive impedance control scheme, which isappropriate for tasks in which the dynamic character of theend-effector/environment interaction must be controlled, and an adaptiveposition/force controller, which is useful for those applications thatrequire independent control of end-effector position and contact force. Thecompliance control strategies retain the simplicity and model independenceof the trajectory tracking scheme upon which they are based, and are shownto ensure uniform boundedness of all signals and arbitrarily accuraterealization of the given compliance control objectives. The capabilities ofthe proposed control strategies are illustrated through computer simulationswith a robot manipulator possessing very flexible joints.     

Sliding Mode Adaptive Neural-Network Control for Nonholonomic Mobile Modular Manipulators

A general mobile modular manipulator can be defined as a m-wheeled holonomic/nonholonomic mobile platform combining with a n-degree of freedom modular manipulator. This paper presents a sliding mode adaptive neural-network controller for trajectory following of nonholonomic mobile modular manipulators in task space. Dynamic model for the entire mobile modular manipulator is established in consideration of nonholonomic constraints and the interactive motions between the mobile platform and the onboard modular manipulator. Multilayered perceptrons (MLP) are used as estimators to approximate the dynamic model of the mobile modular manipulator. Sliding mode control and direct adaptive technique are combined together to suppress bounded disturbances and modeling errors caused by parameter uncertainties. Simulations are performed to demonstrate that the dynamic modeling method is valid and the controller design algorithm is effective.     

不确定性机器人的自适应跟踪控制

提出了一种自适应控制策略 ,用于不确定性机器人的轨迹跟踪 ,该控制器结构简单 ,且无需计算回归矩阵 ,通过对二自由度的机器人的仿真 ,证明该方法能使跟踪误差快速趋近于零     

A Neural Network Adaptive Controller for End-effector Tracking of Redundant Robot Manipulators

In this paper we propose a neural network adaptive controller to achieve end-effector tracking of redundant robot manipulators. The controller is designed in Cartesian space to overcome the problem of motion planning which is closely related to the inverse kinematics problem. The unknown model of the system is approximated by a decomposed structure neural network. Each neural network approximates a separate element of the dynamical model. These approximations are used to derive an adaptive stable control law. The parameter adaptation algorithm is derived from the stability study of the closed loop system using Lyapunov approach with intrinsic properties of robot manipulators. Two control strategies are considered. First, the aim of the controller is to achieve good tracking of the end-effector regardless the robot configurations. Second, the controller is improved using augmented space strategy to ensure minimum displacements of the joint positions of the robot. Simulation examples are also presented to verify the effectiveness of the proposed approach.     

一类不确定非完整动力学系统的时变镇定

对于一类具有未知惯性参数的非完整动力学系统,提出了新的时变自适应镇定律,将其用于一类移动机器人的位姿镇定中．仿真结果验证了所提控制方法的有效性．     

An Adaptive Fuzzy Control Model for Multi-Joint Manipulators

Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required. Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity, coupling and uncertainty. Therefore, the proposed algorithm has good practical application prospects and promotes the development of complex control systems.