Adaptive robust motion/force control of holonomic-constrained nonholonomic mobile manipulators.

In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance and the bounded constraint force. Simulation results validate that the motion of the system converges to the desired trajectory, and the constraint force converges to the desired force.     

Adaptive recurrent neural network control of uncertain constrained nonholonomic mobile manipulators

In this article, motion/force control problem of a class of constrained mobile manipulators with unknown dynamics is considered. The system is subject to both holonomic and nonholonomic constraints. An adaptive recurrent neural network controller is proposed to deal with the unmodelled system dynamics. The proposed control strategy guarantees that the system motion asymptotically converges to the desired manifold while the constraint force remains bounded. In addition, an adaptive method is proposed to identify the contact surface. Simulation studies are carried out to verify the validation of the proposed approach.     

On trajectory tracking control for nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances

This paper studies the trajectory tracking control problem of mobile manipulators subject to nonholonomic constraints, operating in task space, with the presence of external torque disturbances and dynamic uncertainties. The proposed controls are robust to external torque disturbances and can overcome the effects of the unknown dynamic parameters. The stability of the closed-loop system and the asymptotic convergences of tracking errors are proved using Lyapunov synthesis. The proposed control strategies have been designed to drive the system motion converges to the desired manifold and, at the same time, guarantees the boundedness of all the closed-loop signals. Simulation results validate that the system trajectory converge to the desired one.     

一种基于有限时间稳定的环绕控制器设计

针对单无人机对单目标的环航跟踪问题,设计了一个能保证无人机在速度有界条件下,飞行轨迹快速收敛到期望航迹的控制器.1）根据无人机运动特性,设计了一个考虑目标运动状态的控制方案,并利用Lyapunov稳定性定理给出了系统渐近稳定的充分条件.2）结合饱和控制和有限时间控制,得到使无人机相对目标距离在有限时间内收敛到期望值的充分条件.3）用数值算例比较验证了所提控制器的有效性.     

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.     

机械臂的动态混合控制

本文研究当机械臂的终端受有约束时的控制问题,其中心内容是给出“任务规范投影算子”的概念,利用它首先将机械臂的动态方程解耦为两组方程,它们分别描述了运动与约束力,在此基础上给出了机械臂的控制律,使闭环系统跟踪期望的速度与约束力。     

VARIABLE STRUCTURE CONTROL OF TWO MANIPULATORS HANDLING A CONSTRAINED OBJECT

The control of two manipulators handling a constrained object involves the control of the position of the object, the internal force used to grasp the object, and the constraint force due to the constraint surface. The robustness of the controller must be guaranteed when the system faces parameter uncertainties and or external disturbances. In this paper, a variable structure control law is proposed. This controller guarantees the asymptotic convergence of the position of the object, internal force, and constraint force to their desired values when uncertainties on the parameters and external disturbances are present in the system. Simulation results for two planar robots moving an object along a horizontal plane illustrate the fact that the proposed controller achieves the desired asymptotic tracking.     

机器人多指操作的递阶控制

为机器人多指协调操作建立一递阶控制系统.给定一操作任务,任务规划器首先生 成一系列物体的运动速度;然后,协调运动规划器根据期望的物体运动速度生成期望的手指 运动速度和期望的抓取姿态变化;同时,抓取力规划器为平衡作用在物体上的外力,根据当前 的抓取姿态,生成各手指所需的抓取力;最后,系统将手指的期望运动速度与为实现期望抓取 力而生成的顺应速度合并,并通过手指的逆雅可比转化为手指关节运动速度后,由手指的关 节级运动控制器实现手指的运动和抓取力的控制.该控制方法已成功应用于香港科技大学 (HKUST)灵巧手控制系统的开发.实验证明该方法不仅能完成物体轨迹的跟踪控制任务, 而且能完成物体对环境的力控制和力与速度的混合控制.     

机器人多指操作的递阶控制1)

This paper presents a hierarchical control system for robot multifingered coordinate manipulation. Given a manipulation,the task planner generates a sequence of object's motion velocities at first,and then generates for coordinate motion the desired velocities of finger's motion and desired orientation change of the grasped object according to the desired velocities of object's motion.At the same time,the force planner generates the grasp forces on the fingers in order to resist the external forces on the object,according to the grasp posture.Finally,the system generates a result compliance velocity from both the desired finger's velocities and desired grasp forces,and transfers it into joint velocites through the finger's inverse Jacobian.Then the controller of joint motion implements the control of both forces and velocities for the fingers.The approach has been applied to the development of control system HKUST dexterous hand successfully.Experiment results show that it is not only possible to trail and control the object's track,but also possible to realize force control and the hybrid control of both forces and velocities through this method.     

Approximation-based adaptive tracking control of nonlinear pure-feedback systems with time-varying output constraints

An adaptive neural network control problem of completely non-affine pure-feedback systems with a time-varying output constraint and external disturbances is investigated. For the controller design, we presents an appropriate Barrier Lyapunov Function (BLF) considering both the time-varying output constraint and the control direction nonlinearities induced from the implicit function theorem and mean value theorem. From an error transformation, the BLF dependent on the time-varying constraint is transformed into the explicitly time-independent BLF. Based on the explicitly time-independent BLF, an adaptive dynamic surface control scheme using the function approximation technique is designed to ensure both the constraint satisfaction and the desired tracking ability. It is shown that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an adjustable neighborhood of the origin while the time-varying output constraint is never violated.     

Adaptive Force-Motion Control of Coordinated Robots Interacting With Geometrically Unknown Environments

Most studies on adaptive coordination of multi-robot systems assume exact knowledge of system kinematics and deal only with dynamic uncertainties. However, many industrial applications involve tasks in which a multi-robot system interacts with geometrically unknown environments. In this paper, we consider a multi-robot system grasping a rigid object in contact with a geometrically unknown surface. The proposed adaptive hybrid force-motion controller guarantees asymptotic tracking of desired motion and force trajectories while ensuring exact identification of constraint Jacobian matrix without persistency of excitation condition. The control signal is smooth and does not depend on contact force derivative. The proposed adaptive controller is robustified against environmental friction and nonparametric uncertainty in environment geometry. Simulation examples are presented to illustrate the results.     

线性广义系统的迭代学习控制

针对线性时不变广义系统的迭代学习控制问题．利用时间加权范数性质．通过Frobenius范数给出广义系统在D型和PD型闭环学习律作用下系统的实际输出轨迹逐渐逼近理想输出轨迹的充分条件．并指出在D型闭环学习律的基础上加上P型闭环学习律不影响控制系统的收敛性．但可以改变系统的性能．仿真算例说明了该方法的有效性．     

Robust Adaptive Control of Cooperating Mobile Manipulators With Relative Motion

In this paper, coupled dynamics are presented for two cooperating mobile robotic manipulators manipulating an object with relative motion in the presence of uncertainties and external disturbances. Centralized robust adaptive controls are introduced to guarantee the motion, and force trajectories of the constrained object converge to the desired manifolds with prescribed performance. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The tracking of the constraint trajectory/force up to an ultimately bounded error is achieved. The proposed adaptive controls are robust against relative motion disturbances and parametric uncertainties and are validated by simulation studies.     

空间机器人抓捕目标后基于任务相容性的消旋策略

针对双臂空间机器人抓捕自旋目标后的镇定操作,在考虑机器人系统输入约束的条件下,提出了一种基于任务相容性的消旋规划与控制方法。首先,给出空间机器人抓捕目标后的组合系统的动力学模型,作为规划与控制的基础。然后,根据动力学可操作度和任务相容性设计了目标的快速消旋策略,其期望加速度的方向和大小分别取作速度的反方向和机器人系统输入约束允许的最大值。最后,基于所推导的运动学和动力学模型,通过对目标和机械臂末端分别建立柔顺度等式,提出了一种跟踪期望运动轨迹同时对末端接触力进行调节的柔顺控制方法。通过双臂7自由度空间机器人消除目标自旋运动的仿真结果,验证了所提方法的有效性。     

Pursuit formations with dynamic control gains

The paper presents a coordinated motion control law of multiple autonomous agents based on the pursuit strategy with dynamical gains. In particular, we are interested in the control law with no communication between the agents, that is, the leader's moving velocity is not known by the follower robots. Each follower only utilizes its local measurement of relative position information to keep a desired distance and a desired bearing with its neighbors according to a fixed topology. The paper proposes a modified follower's control law, in which each follower pursues its neighbor along the line of sight rotated by a constant offset angle with a dynamic control gain. The offset angle is designed to attain the specific bearing and the dynamic control gain is introduced for the purpose of achieving the desired distance to its neighbor. Then, all the agents make the same motion to the leader's in a steady formation. It is shown that, for the case of uniform rectilinear motion, the group of mobile robots converges to the exact formation specified by the offset angles and the distances no matter what the leader's velocity is, whereas for the case of uniform circular motion, the group of agents converges to an approximation of the formation attained in the rectilinear motion case when the leader's turning radius is much greater than the desired distances between neighboring robots. The effectiveness of the proposed technique and the obtained analytical results are demonstrated in simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

滑模变结构有限时间收敛制导律

针对末端有入射角度约束的制导系统,基于滑模变结构控制思想设计了一种有限时间收敛的滑模制导律,使制导系统的视线角速率快速收敛到零,并令弹道倾角收敛到期望的入射角度.通过非线性控制系统的有限时间稳定性理论对该制导律进行了分析,给出了制导系统有限收敛时间的数学形式,证明了制导系统的有限时间收敛性.最后通过仿真进一步验证了该制导方法的有效性和鲁棒性.     

接触作业型飞行机械臂系统的力/位置混合控制

针对飞行机械臂系统移动接触作业问题,使用了一个力/位置混合控制框架,用以控制飞行器系统持续可靠地接触外部环境同时保持一定大小的接触力,并实现在接触过程中的期望轨迹跟踪.首先将作业空间分成2个子空间--约束空间和自由空间,并分别进行力控制和位置控制.对于力控制问题,证明闭环无人机系统是一个类弹簧-质量-阻尼系统,然后在约束子空间中设计逆动力学控制器来实现接触力控制.自由飞行空间中的运动控制依靠轨迹规划和位置控制器来实现.最后,开发了基于六旋翼飞行机器人的单自由度飞行机械臂系统,在飞行状态下进行接触墙面并跟踪倾斜直线轨迹的实验.结果显示本文所使用方法能够保证在平稳移动的同时控制期望的接触力.     

Passive velocity field control (PVFC). Part I. Geometry androbustness

Passive velocity field control is a control methodology for fully actuated mechanical systems, in which the motion task is specified behaviorally in terms of a velocity field, and the closed-loop system is passive with respect to a supply rate given by the environment power input. The control law is derived geometrically and the geometric and robustness properties of the closed-loop system are analyzed. It is shown that the closed-loop unforced trajectories are geodesics of a closed-loop connection which is compatible with an inertia metric, and that the velocity of the system converges exponentially to a scaled multiple of the desired velocity field. The robustness property of the system exhibits some strong directional preference. In particular, disturbances that push in the direction of the desired momentum do not adversely affect the performance. Moreover, robustness property also improves with more energy in the system     

Robust adaptive control of uncertain force/motion constrained nonholonomic mobile manipulators

In this paper, force/motion tracking control is investigated for nonholonomic mobile manipulators with unknown parameters and disturbances under uncertain holonomic constraints. The nonholonomic mobile manipulator is transformed into a reduced chained form, and then, robust adaptive force/motion control with hybrid variable signals is proposed to compensate for parametric uncertainties and suppress bounded disturbances. The control scheme guarantees that the outputs of the dynamic system track some bounded auxiliary signals, which subsequently drive the kinematic system to the desired trajectory/force. Simulation studies on the control of a wheeled mobile manipulator are used to show the effectiveness of the proposed scheme.     

Control of nonlinear systems with time-varying output constraints

This paper presents control design for strict feedback nonlinear systems with time-varying output constraints. An asymmetric time-varying Barrier Lyapunov Function (BLF) is employed to ensure constraint satisfaction. By allowing the barriers to vary with the desired trajectory in time, the initial condition requirements are relaxed. Through a change of tracking error coordinates, we eliminate the explicit dependence of the BLF on time, thereby simplifying the analysis of constraint satisfaction. We show that asymptotic output tracking is achieved without violation of the output constraint, and also quantify the transient performance bound as a function of time that converges to zero. To handle parametric model uncertainty, we present an adaptive controller that ensures constraint satisfaction during the transient phase of online parameter adaptation. The performance of the proposed control is illustrated through a simulation example.