基于位置约束的两轮驱动机器人路径跟踪控制方法

两轮驱动机器人的应用越来越广泛,但由于两轮驱动机器人属于欠驱动系统,输入量不能使机器人按任意轨迹运动,因此较难控制。针对两轮驱动机器人的路径跟踪控制问题,分析了两轮驱动机器人运动模型,提出了一种新的路径跟踪控制方法。通过左右轮的双闭环PID控制来约束两轮机器人的速度和位姿,同时,在期望路径附近建立矢量场,引入位置约束,促使两轮机器人在偏离期望路径时能够快速回归,完成路径跟踪任务。搭建了两轮驱动机器人硬件实验平台,实现了两轮驱动机器人的路径跟踪控制。实验结果表明,两轮驱动机器人能够准确跟踪期望路径,对于设置的一种较复杂路径跟踪实验,得出的各跟踪点的相对误差的均方差为0.86%,最大相对误差为3.64%。     

3-PRS并联机器人惯量耦合特性研究

惯量是影响机器人动态性能的主要因素,并联机器人因其多支链耦合的结构特点,关节空间各驱动轴出现惯量耦合的动力学特性,在高速、高加速度运动时易引起控制超调、振动等现象,破坏机器人的动态性能,因此研究并联机器人惯量耦合特性具有重要意义. 以3-PRS 并联机器人为例,通过虚功原理求得惯量矩阵,提出惯量耦合指标,该耦合指标表征了并联机器人在工作空间不同位姿时各驱动轴的耦合惯量大小,并给出了该耦合指标在机器人工作空间内的分布规律. 进一步在一台3-PRS 并联机器人样机上进行了实验验证,结果表明耦合惯量会改变驱动轴负载,负载的改变将最终影响动态性能. 同时各驱动轴的负载变化量随着惯量耦合指标的变大而变大,与理论分析有较好的一致性. 研究成果可帮助评价并联机器人的动力学耦合特性,并可用于并联机器人的结构参数优化及伺服参数调试以提高机器人的动态性能.      

单足机器人周期跳跃控制的虚拟约束方法

 研究单足机器人周期跳跃控制问题．弹簧支撑倒立摆模型可以比较准确地描述动物的跳跃行为，但无控制的自然跳跃抗干扰能力较差，一般采用轨迹跟踪控制方法实现单足机器人周期跳跃．当系统存在比较大的误差时，传统的时间轨迹跟踪控制方法存在明显的不足．引入虚拟约束技术，采用基于空间路径跟踪的控制方法可以克服时间轨迹跟踪的不足．采用点足机器人模型，并通过控制腿伸缩的方式为系统提供动力，将跳跃过程分为地面摆动和腾空飞行两个阶段，并通过起飞和着陆两个事件完成两个阶段之间的转换，整个系统模型属于欠驱动非光滑动力学系统．根据简化的动力学方程获得系统的虚拟约束解析表达式，并采用部分反馈线性化方法结合PD 控制设计系统的控制律．分析了系统的混合零动力学方程，并证明了闭环系统的临界稳定性．仿真结果表明，提出的控制方法可以实现单足机器人的周期跳跃控制，并且对外部干扰具有较强的鲁棒性．     

基于步态切换的欠驱动双足机器人控制方法

由于高维、非线性、欠驱动等特点,3-D双足机器人的稳定性控制依然是一个研究难点.一些传统的控制方法,如基于事件的反馈控制方法和PD控制方法,抗扰动能力较弱,鲁棒性较差.通过观察,人类受到外部扰动影响时,会通过调整步态重新获得稳定性,相较之下仅依靠一个步态获得的稳定性是有限的.受此启发,本文针对上述问题提出一种基于步态切换的欠驱动3-D双足机器人控制方法.首先,以能耗最少为优化目标,通过非线性优化方法预先设计多组不同步长、步速的步态作为参考步态,以构建一个步态库;然后,通过综合考虑步态切换过程中的稳定性与能效,建立了多目标步态切换函数;最后,将该步态切换函数作为优化目标,并求解该最小化问题获得下一步的参考步态,从而实现步态切换,达到使用步态库-多轨迹方法来提高鲁棒性的目的.在仿真实验中运用该步态切换控制方法,欠驱动3-D双足机器人可实现相对高度在[-20,20]mm内随机变化的不平整地面上行走,而仅采用单步态控制策略则无法克服这样的外部扰动,从而说明了基于步态切换的欠驱动双足机器人控制方法的有效性.     

迭代学习型瞬时最优控制及其收敛性分析

将传统的瞬时最优化控制和智能算法中的迭代学习控制相结合,提出了基于最优化控制算法和智能控制算法的迭代学习型瞬时最优化控制算法.该方法以线性系统为模型,以系统的响应与期望响应的差值为反馈,以二次型性能泛函为目标函数,通过迭代学习修正主动控制器的控制信号,提高主动控制的效果.针对迭代学习型瞬时最优化控制算法迭代的特性,本文采用范数方法给出了该方法收敛的充分条件.为验证方法的有效性,选取第二代基准模型作为计算模型,埃尔森特罗地震波南北分量作为输入载荷,数值仿真结果表明,迭代学习型瞬时最优控制算法较传统的瞬时最优控制算法有更好的控制效果.     

双臂空间机器人关节空间的补偿学习控制

在载体位置与姿态均不受控制情况下,结合动量(矩)守恒关系对系统进行了运动学、动力学的分析,得到了漂浮基双臂空间机器人的系统动力学方程.采用PD控制的计算力矩法,得到了系统的闭环动态误差方程,在此基础上设计了针对不确定性的自由漂浮空间机器人的控制方案,提出了一种基于遗传算法的补偿学习控制方法.将补偿学习控制与计算力矩法相结合,利用遗传算法的进化学习消除不确定因素的影响,实现机器人轨迹跟踪的良好控制.     

美国激光驱动X光背光源研究综述

激光驱动X光背光技术伴随着高功率激光技术和ICF的发展而发展，它既与激光装置性能密切相关，也与不断升级的物理需求相联系。介绍了美国激光驱动X光背光源发展的两个阶段，对每个阶段的主要研究内容和应用情况进行了详细的总结和分析，对PTS装置上激光驱动X光背光源的激光装置设计提出了要求，并对激光驱动X光背光源的研究提出了建议。     

基于步态切换的欠驱动双足机器人控制方法

由于高维、非线性、欠驱动等特点, 3-D双足机器人的稳定性控制依然是一个研究难点. 一些传统的控制方法, 如基于事件的反馈控制方法和PD控制方法, 抗扰动能力较弱, 鲁棒性较差. 通过观察, 人类受到外部扰动影响时, 会通过调整步态重新获得稳定性,相较之下仅依靠一个步态获得的稳定性是有限的. 受此启发, 本文针对上述问题提出一种基于步态切换的欠驱动3-D双足机器人控制方法. 首先, 以能耗最少为优化目标, 通过非线性优化方法预先设计多组不同步长、步速的步态作为参考步态, 以构建一个步态库; 然后, 通过综合考虑步态切换过程中的稳定性与能效, 建立了多目标步态切换函数; 最后, 将该步态切换函数作为优化目标, 并求解该最小化问题获得下一步的参考步态, 从而实现步态切换, 达到使用步态库?多轨迹方法来提高鲁棒性的目的. 在仿真实验中运用该步态切换控制方法, 欠驱动3-D双足机器人可实现相对高度在[-20, 20] mm内随机变化的不平整地面上行走, 而仅采用单步态控制策略则无法克服这样的外部扰动, 从而说明了基于步态切换的欠驱动双足机器人控制方法的有效性.      

振动轮式微机械陀螺仪模态控制方法研究

振动轮式微机械陀螺仪存在两个主要的工作模态 :驱动模态和敏感模态。本文研究了敏感模态反馈控制环节对系统工作性能的影响。提出刚度、阻尼组合反馈的模态控制思想 ,探讨了利用刚度反馈控制敏感模态的固有谐振频率 ,利用阻尼反馈控制系统检测范围的多参量控制方法 ;并对敏感模态中刚度反馈校正环节和阻尼反馈的校正环节进行了详细的分析 ,建立了系统对两个校正环节在增益和相位上的要求。     

柔性机械臂动力学方程单向递推组集方法

本文基于Jourdain变分原理提出一种柔性机械臂动力学方程的单向递推组集方法。用规则标号法描述系统中物体和铰的邻接关系;用铰相对坐标和模态坐标分别描述物体的大位移运动和弹性变形。文末以三连杆机器人操作手为例说明本文建模的过程。     

Nonlinear robust and optimal control of robot manipulators

In this paper, we propose a new optimal control method for robust control of nonlinear robot manipulators. Many industrial robot systems are required to perform relatively large angular movement with sufficient accuracy. In real circumstances, highly nonlinear manipulator dynamics and uncertainties such as unknown load placed on the manipulator, external disturbance, and joint friction make the precise control of manipulators a very challenging task. The main contribution of this work is to develop a new robust control strategy to accomplish the precise control of robot manipulators under load uncertainty using a nonlinear optimal control formulation and solution. This methodology is based on the underlying relation between the robust stability and performance optimality. A class of robust control problems can be transformed to an equivalent optimal control problem by incorporating the uncertainty bounds into the cost functional. The θ-D optimal control approach is utilized to find an approximate closed-form feedback solution to the resultant nonlinear optimal control problem via a perturbation process. Numerical simulations show that the proposed robust controller is able to control the robot manipulator precisely under large load variations.     

Decentralized direct adaptive fuzzy control of robots using voltage control strategy

Decentralized control is the most favorite control of robot manipulators due to computational simplicity and ease of implementation. Beside that, adaptive fuzzy control efficiently controls uncertain nonlinear systems. These motivate us to design a decentralized fuzzy controller. However, there are some challenging problems to guarantee stability. The state-space model of the robotic system including the robot manipulator and motors is in a noncompanion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. For this purpose, adaptive fuzzy control may use all variable states. As a result, it suffers from computational burden. To overcome the problems, we present a novel decentralized Direct Adaptive Fuzzy Control (DAFC) of electrically driven robot manipulators using the voltage control strategy. The proposed DAFC is simple, in a decentralized structure with high-accuracy response, robust tracking performance, and guaranteed stability. Instead of all state variables, only the tracking error of every joint and its derivative are given as the inputs of the controller. The proposed DAFC is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results verify superiority of the decentralized DAFC to a decentralized PD-fuzzy controller.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

An evolutionary approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.     

Achievement of chaotic synchronization trajectories of master–slave manipulators with feedback control strategy

This paper addresses a master-slave synchro- nization strategy for complex dynamic systems based on feedback control. This strategy is applied to 3-DOF pla- nar manipulators in order to obtain synchronization in such complicated as chaotic motions of end-effectors. A chaotic curve is selected from Duffing equation as the trajectory of master end-effector and a piecewise approximation method is proposed to accurately represent this chaotic trajectory of end-effectors. The dynamical equations of master-slave manipulators with synchronization controller are derived, and the Lyapunov stability theory is used to determine the stability of this controlled synchronization system. In numer- ical experiments, the synchronous motions of end-effectors as well as three joint angles and torques of master-slave manipulators are studied under the control of the proposed synchronization strategy. It is found that the positive gain matrix affects the implementation of synchronization con- trol strategy. This synchronization control strategy proves the synchronization＇s feasibility and controllability for com- plicated motions generated by master-slave manipulators.     

Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators

This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tracking control of robotic manipulators. The proposed controller is model-free in the form of discrete Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned using an adaptive mechanism derived by stability analysis. A robust control term is used to compensate the approximation error of the fuzzy system for asymptotic tracking of a desired trajectory. The controller is robust against all uncertainties associated with the robot manipulator and actuators. It is easy to implement since it requires only the joint position feedback. Compared with fuzzy controllers which employ all states to guarantee stability, the proposed controller is very simpler. Stability analysis and simulation results show its efficiency in the tracking control.     

Control and Parameter Optimization of Flexible Robots*

A hierarchical control concept for flexible robot manipulators is presented. The equations of motion are derived using the multibody system method, incorporating flexible links equipped with surface bonded actuating and sensing devices. Exploiting the structure of the dynamic model, the control concept allows combination of any joint level control for the gross motion of the manipulator with decentralized linear control of the elastic deformation of each flexible link. Therefore, the approach is capable of solving both the problem of fast and precise point-to-point motion, with acceptable vibration characteristics, and the problem of accurate trajectory tracking of the end-effector. Control parameters are found through parameter optimization. In order to verify the proposed control strategy, a SCARA robot with one flexible link is considered.     

Free-floating closed-chain planar robots: Kinematics and path planning

The study of free-floating manipulators is important for the success of robotics program in space and in the design of innovative robot systems which can operate over a large workspace. In order to study the fundamental theoretical and experimental issues encountered in space robotics, a closed-chain planar manipulator was built at Ohio University (OU) which floats on a flat table using air bearings. Due to the absence of external forces in the plane of the table and couples normal to this plane, the linear momentum in the plane and the angular momentum normal to this plane are conserved. It is well known that the linear momentum equations are holonomic while the angular momentum equation is nonholonomic. Due to this nonholonomic behavior, the path-planning schemes commonly used for fixed-base manipulators do not directly apply to free-floating manipulators. In this paper, we present an algorithm for motion planning of planar free-floating manipulators based on the inverse position kinematics of the mechanism. It is demonstrated that the inverse position kinematics algorithms, commonly used for fixed-base manipulators, can be successfully applied to free-floating manipulators using an iterative search procedure to satisfy the nonholonomic angular momentum constraints. This procedure results in paths identical to those predicted by inverse rate kinematics. The inverse position kinematics algorithm is then used to avoid singularities during motion to result in successful paths. The results of the simulation of this algorithm using parameter estimates of the OU free-floating robot are presented.     

柔性铰柔性杆机器人动力学建模、仿真和控制

本文探究了铰柔性对机器人动力学响应和动力学控制的影响. 首先, 建立由$n$个柔性铰和$n$个柔性杆组成的空间机器人模型, 运用递推拉格朗日动力学方法, 得到柔性机器人系统的刚柔耦合动力学方程. 在动力学建模过程中, 除了考虑杆件的拉伸变形、弯曲变形、扭转变形以及非线性耦合变形对机器人系统动力学行为的影响, 还考虑了铰的柔性对机器人动力学响应和控制的影响. 其中, 柔性铰模型是基于Spong的柔性关节简化模型, 将柔性铰看成线性扭转弹簧, 不仅考虑了铰阻尼的存在, 还考虑了柔性铰的质量效应. 其次, 编写了空间柔性铰柔性杆机器人仿真程序, 研究铰的刚度系数和阻尼系数对系统动力学响应的影响. 研究表明: 随着柔性铰刚度系数的增大, 柔性机器人的动态响应幅值减小, 振动频率变大. 随着柔性铰阻尼系数的增大, 柔性机器人的动态响应幅值减小, 振动幅值的衰减速度变快. 可通过调节柔性铰的刚度和阻尼来减小柔性铰柔性杆机器人的振动, 因此铰阻尼的研究具有重要工程意义. 最后, 研究了铰柔性在机器人系统动力学控制中的影响. 在刚性铰机械臂和柔性铰机械臂完成相同圆周运动时, 通过逆动力学方法求解得到两种情况下的关节驱动力矩. 研究表明: 引入柔性铰会使控制所需的驱动力矩变小, 对机器人控制的影响显著.