基于最小无穷范数的蛇形机器人最优力矩控制

带有被动轮的蛇形机器人在跟踪头部轨迹时,力矩输入具有无穷多解,其中振幅最小的解对应着电动机额定扭矩最小的情况,即为本文所指的优化力矩.由于带有被动轮的蛇形机器人侧向不打滑时轮子的法向速度为0,每个模块可以引入一个速度约束,此时蛇形机器人是一个非完整约束系统,而振幅最小的力矩对应着具有最小无穷范数的力矩.通过建立非完整约束动力学方程,将求解振幅最小的力矩转化为在动力学方程约束下求解最小无穷范数的问题.利用最小无穷范数的数值算法求得在蛇形机器人跟踪头部速度时的关节力矩最小无穷范数解,从而利用最小无穷范数解对蛇形机器人进行力矩控制,实现力矩振幅最小的最优力矩控制.动力学数值仿真结果证明了算法的有效性.     

基于改进蛇形曲线的蛇形机器人在流场中避障的轨迹跟踪控制律

针对蛇形机器人在流场中各关节之间的轨迹跟踪问题,研究一种基于改进蛇形曲线的蛇形机器人在流场中避障的轨迹跟踪控制律.首先,考虑流体环境可能施加在蛇形机器人系统上的外部干扰,采用浸入边界-格子Boltzmann方法(IB-LBM)在流场中建立障碍通道和蛇形机器人的流固耦合模型.然后,对蛇形机器人加入势函数,使其可以避开障碍;并采用改进的蛇形曲线方程使机器人尾部各关节跟踪头部的运动轨迹.最后,通过Matlab仿真和实验,研究不同流场密度、机器人尾部摆动频率以及流场雷诺数等参数对蛇形机器人轨迹跟踪的影响.理论分析和数值仿真表明,所设计的轨迹跟踪控制律不仅可以使蛇形机器人在遇到障碍时各关节跟踪前一关节的运动轨迹,而且还能使横向距离、纵向距离及方向角趋于稳定,达到有效避障的目的.此外,蛇形机器人在离开障碍通道后,各关节可以恢复蛇形曲线的运动形式,为蛇形机器人提供源源不断的前进动力.仿真和实验结果验证了轨迹跟踪控制律的有效性.     

人机不确定条件下康复步行训练机器人的部分记忆迭代学习限速控制

为了提高康复步行训练机器人的跟踪精度及安全性,提出了一种带有运动速度约束和部分记忆信息的自适应迭代学习控制方法,目的是抑制人机不确定性及速度突变对系统跟踪性能的影响.在考虑人机不确定性的基础上,建立了康复步行训练机器人的动力学模型.提出了基于模型预测的速度约束方法,通过限制每个轮子的运动速度,约束了机器人的实际运动速度.进一步,利用受约束的运动速度建立了动力学跟踪误差系统,提出了具有部分记忆信息的自适应迭代学习控制器设计方法,并验证了跟踪误差系统的稳定性.仿真对比分析和实验研究结果表明,文中提出的控制方法能抑制人机不确定性并使康复者在安全速度下完成步行训练.     

蜿蜒步态下的蛇形机器人路径跟踪控制研究

在面向灾区救援等针对蛇形机器人蜿蜒运动的直线路径跟踪效果差的问题,本项目提出基于滑模控制理论的方向控制器,有效收敛了蛇形机器人在稳态时的运动误差。针对蛇形机器人头部晃动影响头部传感器获取有效数据的难题,创新地提出基于补偿函数的头部控制方法,使得蛇头的运动方向与蛇身整体的运动方向一致,保证了蛇头相机拍摄的可读性和传感器测量的准确性,便于机器人准确地感知环境,确保在转弯时机器人整体呈蛇形曲线。     

农田信息采集机器人机构设计与奇异性分析

提出一种四轮并联机构的新型农田信息采集机器人．结构和越障原理分析结果表明,该机器人具有较 强的地形适应能力．为了研究机器人的奇异位形,根据雅可比矩阵的定义和D-H 矩阵法直接求出雅可比矩阵的解析 表达．根据机构的奇异性分类,利用动力学分析软件ADAMS 仿真得到了各奇异位形的精确位置和运动特点,与理 论分析相一致．根据以上分析设计的机器人物理样机能有效避免奇异位形．     

受非完整约束移动机器人的跟踪控制

讨论受非完整约束移动机器人运动学模型和动力学模型的跟踪控制问题.通过把它 们化成统一的标准型,提出了新的动态跟踪控制器.这些控制器具有维数低和没有奇异点的 优点.仿真结果表明了所提出控制方法的有效性.     

基于主动偏心轮的全方位移动机器人航位推算与跟踪控制

针对基于主动偏心轮的全方位移动机器人系统,提出了一种基于冗余码盘的航位推算方法和一种具有饱和约束的轨迹跟踪控制器.具体而言,首先分析了车轮发生滑动的原因,考虑到机器人随动轮相对于主动轮不易打滑的特性,设计了具有冗余码盘的随动轮结构.基于该结构,将机器人航位推算转化为一个含约束的最小二乘问题.实验结果表明:与未考虑随动轮约束的传统方法相比,该方法降低了轮子打滑的影响,提高了航位推算的精度.考虑到实际机器人系统的速度控制量具有上限,基于李亚普诺夫方法设计了含饱和约束的轨迹跟踪控制器,并对其稳定性和有界性进行证明.仿真与实验结果表明本文提出的控制器具有良好的性能,同时能够满足控制量的饱和约束.     

基于连续体模型的蛇形机器人质心速度跟踪控制方法

基于连续体模型合理简化蛇形机器人的动力学方程,基于该动力学描述获得无侧滑条件下使机器人质心速度稳定的关节角度参数集.然后,通过分析侧滑概率与控制参数之间的关系,获得法向摩擦力有限时使质心速度稳定的控制参数.在实现质心速度稳定的基础上,基于连续体模型获得无侧滑时实现机器人速度跟踪的控制参数.最后基于上述理论值设计控制器,将上述理论值作为关节角度参数的初值,利用速度反馈对关节角度进行微调节,消除模型近似和环境差异带来的速度误差.基于Open Dynamics Engine进行仿真,仿真结果显示蛇形机器人质心速度能够跟踪期望速度,从而验证了所提方法的有效性.     

基于迭代学习控制的鳗鱼机器人切向速度跟踪控制

鳗鱼机器人的动力学模型非线性强、高度欠驱动,导致多关节鳗鱼机器人的切向速度跟踪控制极具挑战．本文采用P型迭代学习控制与步态生成器相结合的方法对多关节鳗鱼机器人的切向速度进行跟踪控制．首先,采用解析牛顿-欧拉法建立非惯性系下的鳗鱼机器人动力学模型,直接获得切向速度子动力学模型;然后,利用带饱和函数的P型迭代学习控制器控制步态参数,并且利用复合能量函数和切向速度子动力学模型分析该控制器的收敛性,得到切向速度跟踪误差的收敛条件;最后,提出鳗鱼机器人的运动控制框架,并对多模块的鳗鱼机器人进行仿真和实验．实验结果表明,实际的切向速度随着迭代次数的增加而逐渐跟踪上了期望的切向速度,故而验证了鳗鱼机器人切向速度跟踪控制器的有效性．     

基于扰动观测器的机器人自适应神经网络跟踪控制研究

为解决机器人动力学模型未知问题并提升系统鲁棒性,本文基于扰动观测器,考虑动力学模型未知的情况,设计了一种自适应神经网络（Neural network,NN）跟踪控制器.首先分析了机器人运动学和动力学模型,针对模型已知的情况,提出了刚体机械臂通用模型跟踪控制策略;在考虑动力学模型未知的情况下,利用径向基函数（Radial basis function,RBF）神经网络设计基于全状态反馈的自适应神经网络跟踪控制器,并通过设计扰动观测器补偿系统中的未知扰动.利用李雅普诺夫理论证明所提出的控制策略可以使闭环系统误差信号半全局一致有界（Semi-globally uniformly bounded,SGUB）,并通过选择合适的增益参数可以将跟踪误差收敛到零域.仿真结果证明所提出算法的有效性并且所提出的控制器在Baxter机器人平台上得到了实验验证.     

电驱移动机器人多变量固定时间连续编队控制

针对扰动下电驱动非完整移动机器人固定时间编队控制问题,通过引入包含驱动器动力学的领航者-跟随者状态空间动力学模型,分两步对编队控制器进行了设计。对领航者跟随者编队运动学模型进行了多变量固定时间控制设计。在动力学层面,为实现扰动下的速度跟踪,通过辅助输入设计了一种跟随者机器人多变量超螺旋固定时间连续电压控制器。所提算法使机器人编队克服了跟随者机器人所受干扰,确保了跟随者机器人与领航者在固定时间达到期望队形,跟随者在固定时间内跟随期望速度,设计的连续控制消除了开关控制的抖振现象。通过参数设计提前给定系统收敛的固定时间,与系统初始状态无关。基于Lyapunov方法进行了系统稳定性分析。通过仿真对算法进行了验证。     

Balancing and Trajectory Tracking of Two-Wheeled Mobile Robot Using Backstepping Sliding Mode Control: Design and Experiments

The key attributes of Two Wheeled Balancing Mobile Robots (TWBMRs) are nonholonomic constraints and inherent instability. This paper deals with the problem of balancing and trajectory tracking of TWBMR using backstepping Sliding Mode Controller (SMC). First, the mathematical representation of TWBMR is derived using Lagrangian method by incorporating the dynamics of DC motors. Then, a decoupling approach is applied for simplifying the dynamic equations. The backstepping SMC technique is finally adopted to achieve the balancing and trajectory tracking of the TWBMR, whereas both model uncertainties and exogenous disturbance are taken into account in the controller design methodology. In order to determine the velocity, the trajectory tracking is achieved by the kinematic control, which is a common backstepping controller. For the velocity convergence of TWBMR to the generated desired value, two SMCs are designed, in which the motors voltage are directly controlled as the control laws. Simplicity in practical implementation and control law, ability to overcome uncertainties and appropriate performance are the main advantages of the proposed controller. The effectiveness of the proposed controller is verified through simulation and experimental results.     

Tracking Control for a Cushion Robot Based on Fuzzy Path Planning With Safe Angular Velocity

This study proposes a new nonlinear tracking control method with safe angular velocity constraints for a cushion robot. A fuzzy path planning algorithm is investigated and a realtime desired motion path of obstacle avoidance is obtained. The angular velocity is constrained by the controller, so the planned path guarantees the safety of users. According to Lyapunov theory, the controller is designed to maintain stability in terms of solutions of linear matrix inequalities and the controller's performance with safe angular velocity constraints is derived. The simulation and experiment results confirm the effectiveness of the proposed method and verify that the angular velocity of the cushion robot provided safe motion with obstacle avoidance.      

多机器人主—从行星式编队控制

研究了二阶积分器描述的多机器人主—从行星式编队控制问题,提出了将多机器人编队分解为每个机器人对各自具有时变速度的虚拟机器人的跟踪控制,使得每个机器人相对于虚拟机器人的位置与速度跟踪误差收敛为零且彼此不相碰撞,此时编队系统收敛到理想队形.在统一的算法框架下,分别实现了跟随者以领航者为中心的公转运动编队(revolution formation,RF)模式和跟随者与领航者保持期望距离、期望速度的编队(desiredformation,DF)模式.公转运动编队(RF)模式适用于异构多机器人系统的环境探索任务;保持期望距离、期望速度的编队(DF)模式适用于自主水下机器人(AUV)、无人机(UAV)等合作与协调任务.应用李亚普诺夫稳定性理论对控制算法的稳定性进行了分析,并通过计算机仿真验证了该方法的有效性.     

Adaptive controller design for underwater snake robot with unmatched uncertainties

Because of hydrodynamic model error of the present dynamic model, there is a challenge in controller design for the underwater snake-like robot. To tackle this challenge, this paper proposes an adaptive control schemes based on dynamic model for a planar, underwater snake-like robot with model error and time-varying noise. The adaptive control schemes aim to achieve the adaptive control of joint angles tracking and the direction of locomotion control. First, through approximation and reducibility using Taylor expansion method, a simplified dynamics model of a planar amphibious snake-like robot is derived. Then, the L1 adaptive controller based on piecewise constant adaptive law is applied on the simplified planar, underwater snake-like robot, which can deal with both matched and unmatched nonlinear uncertainties. Finally, to control the direction of locomotion, an auxiliary bias signal is used as the control input to regulate the locomotion direction. Simulation results show that this L1 adaptive controller is valid to deal with different uncertainties and achieve the joint angles tracking and fast adaptive at the same time. The modified L1 adaptive controller, in which the auxiliary bias item is added, has the ability to change the direction of locomotion, that is, the orientation angle is periodic with arbitrarily given constant on average.     

Modeling and Control of Head Raising Snake Robots by Using Kinematic Redundancy

In this paper, we consider trajectory tracking control of a head raising snake robot on a flat plane by using kinematic redundancy. We discuss the motion control requirements to accomplish trajectory tracking and other tasks, such as singular configuration avoidance and obstacle avoidance, for the snake robot. The features of the internal motion caused by kinematic redundancy are considered, and a kinematic model and a dynamic model of the snake robot are derived by introducing two types of shape controllable point. The first is the head shape controllable point, and the other is the base shape controllable point. We analyzed the features of the two kinds of shape controllable point and proposed a controller to accomplish the trajectory tracking of the robot’s head as its main task along with several sub-tasks by using redundancy. The proposed method to accomplish several sub-tasks is useful for both the kinematic model and the dynamic model. Experimental results using a head raising snake robot which can control the angular velocity of its joints show the effectiveness of the proposed controller.     

Dynamic modeling and nonlinear tracking control of a novel modified quadrotor

In this article, a nonlinear tracking controller is designed based on Lyapunov stability for a novel aerial robot. The proposed 6‐rotor configuration improves stability and payload lifting capacity of the robot compared with conventional quadrotors while avoiding further complexities in the robot dynamics and steering principles. The dynamical model of the robot is derived using Newton‐Euler method. The model represents a nonlinear, coupled, and underactuated system. The proposed control strategy includes 2 main parts: an attitude controller and a position controller. Both the attitude and position controls are Lyapunov‐based nonlinear tracking controllers that guarantee the asymptotic convergence of the states' tracking errors to zero. Simulation results are presented to illustrate appropriate performance of the closed‐loop system in terms of position/attitude tracking even in the presence of wind disturbance.     

基于自适应和神经动力学的轮式移动机器人路径跟踪控制(英文)

本文提出一种自适应和神经动力学相结合的轮式移动机器人路径跟踪控制方法.首先,设计运动学控制器用来获得机器人期望速度;其次,考虑机器人动力学模型参数的不确定性,利用模型参考自适应方法来设计动力学控制规律,使得机器人实际速度渐近逼近期望值;再次,为克服速度和力矩的跳变,加入神经动力学模型对控制器进行优化,并且通过Lypunov理论来证明整个控制系统的稳定性;最后仿真结果表明该控制方法的有效性.     

Design of a sliding mode controller for an automatic guided vehicle and its implementation

In this paper, a control scheme that combines a kinematic controller and a sliding mode dynamic controller with external disturbances is proposed for an automatic guided vehicle to track a desired trajectory with a specified constant velocity. It provides a method of taking into account specific mobile robot dynamics to convert desired velocity control inputs into torques for the actual mobile robot. First, velocity control inputs are designed for the kinematic controller to make the tracking error vector asymptotically stable. Then, a sliding mode dynamic controller is designed such that the mobile robot’s velocities converge to the velocity control inputs. The control law is obtained based on the backstepping technique. System stability is proved using the Lyapunov stability theory. In addition, a scheme for measuring the errors using a USB camera is described. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controller.