Velocity field control of a class of electrically-driven manipulators

This article addresses the control of robotic manipulators under the assumption that the desired motion in the operational space is encoded through a velocity field. In other words, a vectorial function assigns a velocity vector to each point in the robot workspace. Thus, the control objective is to design a control input such that the actual operational space velocity of the robot end-effector asymptotically tracks the desired velocity from the velocity field. This control formulation is known in the literature as velocity field control. A new velocity field controller together with a rigorous stability analysis is introduced in this article. The controller is developed for a class of electrically-driven manipulators. In this class of manipulators, the passivity property from the servo-amplifier voltage input to the joint velocity is not satisfied. However, global exponential stability of the state space origin of the closed-loop system is proven. Furthermore, the closed-loop system is proven to be and output strictly passive map from an auxiliary input to a filtered error signal. To confirm the theoretical conclusions, a detailed experimental study in a two degrees-of-freedom direct-drive manipulator is provided. Particularly, experiments consist of comparing the performance of a simple PI controller and a high-gain PI controller with respect to the new control scheme.     

Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space

A neural-network-based motion controller in task space is presented in this paper. The proposed controller is addressed as a two-loop cascade control scheme. The outer loop is given by kinematic control in the task space. It provides a joint velocity reference signal to the inner one. The inner loop implements a velocity servo loop at the robot joint level. A radial basis function network （RBFN） is integrated with proportional-integral （PI） control to construct a velocity tracking control scheme for the inner loop. Finally, a prototype technology based control system is designed for a robotic manipulator. The proposed control scheme is applied to the robotic manipulator. Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.     

A practical PID regulator with bounded torques for robot manipulators

This paper proposes a saturated nonlinear PID regulator for industrial robot manipulators. Our controller considers the natural saturation problem given by the output of the control computer, the saturation phenomena of the internal PI velocity controller in the servo driver, and the actuator torque constraints of the robot manipulator. An approach based on the singular perturbations method is used to analyze the exponential stability of the closed-loop system. Experimental essays show the feasibility of the proposed controller. Furthermore, the theoretical results justify why the classical PID used in industrial robots preserves its exponential stability despite the saturation effects of the electronic control devices and the actuator torque constraints.     

Adaptive tracking control of flexible‐joint manipulators without overparametrization

In this paper, an adaptive controller is designed for rigid‐link flexible‐joint robot manipulators based on link and actuator position measurements only. It is based on the adaptive integrator backstepping method and the link and actuator velocity filters are used to estimate the unknown velocity terms. Moreover, the proposed controller exploits the estimate of the joint stiffness matrix inverse to overcome the overparametrization problem, which has been a significant drawback in adaptive partial state feedback controllers. It achieves asymptotic tracking of link positions while keeping all states and signals bounded. The tracking capability of the presented method is shown through simulation results of one‐ and two‐link flexible joint manipulators. © 2004 Wiley Periodicals, Inc.     

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

This paper proposes a new adaptive trajectory tracking control scheme of the wheeled mobile robot without longitudinal velocity measurement. First, based on a kinematic controller, we obtain a new tracking error equation, which is suitable to develop an adaptive controller. Then, we develop a new adaptive trajectory tracking controller, which does not need any accurate values of the wheeled mobile robot parameters, including the driving motor parameters. Moreover, as the longitudinal velocity measurement is still difficult, this controller is developed without longitudinal velocity measurement. In addition, this new adaptive controller introduces a method to improve the control performance. The stability of the closed‐loop system is presented using the direct Lyapunov method. Finally, numerous simulations verify the effectiveness of the new controller.     

Robust saturation‐based control of bilateral teleoperation without velocity measurements

This paper addresses the control design problem under no velocity measurements for nonlinear teleoperation system in the presence of asymmetric time‐varying delays. Based on the proposed proportional‐derivative‐like controller and nonlinear‐proportional‐derivative‐like controller, which correspond, respectively, to the actuator non‐saturation and actuator saturation, the control objectives of boundedness of velocities and position tracking errors for the master robot and the slave robot are obtained. These designed controllers do not rely on the velocity signals. The effectiveness of the proposed controller are finally verified by two numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.     

小型仿人机器人控制系统设计

本文提出了一种以ARM9为主控制器的新型的仿人机器人分布式控制系统。单片机和外部计数器组成关节控制器。主控制器和关节控制器之间采用USB通信。从而实现了控制系统的小型化和低功耗。通过该系统控制小型仿人机器人完成了行走实验。     

A Stable Output Feedback Position Control With Integral Action For Robot Manipulators

In this paper, the problem of robust regulation of robot manipulators using only position measurements is addressed. The main idea of the control design methodology is to use an observer to estimate simultaneously the velocity and the modeling error signal induced by model/system mismatches. The controller is obtained by replacing the velocity and the modeling error in an inverse dynamics feedback by their estimates, which leads to a certainty equivalence controller. The resulting controller has a PID‐type structure which, under least prior knowledge, reduces to the PI₂D regulator studied in [20]. Moreover, the controller is endowed with a natural antireset windup (ARW) scheme to cope with control torque saturations. Regarding the closed‐loop behavior, it is proven that the region of attraction can be arbitrarily enlarged with high observer gains only, thus we prove semiglobal asymptotic stability. Our result supersedes previous works in the direction of performance estimates; specifically, it is also proven that the performance induced by a saturated inverse dynamics controller can be recovered by our PID‐type controller. In this sense, our work reveals some connections between PID‐type and inverse dynamics controllers.     

Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

Many robot controllers require not only joint position measurements but also joint velocity measurements; however, most robotic systems are only equipped with joint position measurement devices. In this paper, a new output feedback tracking control approach is developed for the robot manipulators with model uncertainty. The approach suggested herein does not require velocity measurements and employs the adaptive fuzzy logic. The adaptive fuzzy logic allows us to approximate uncertain and nonlinear robot dynamics. Only one fuzzy system is used to implement the observer-controller structure of the output feedback robot system. It is shown in a rigorous manner that all the signals in a closed loop composed of a robot, an observer, and a controller are uniformly ultimately bounded. Finally, computer simulation results on three-link robot manipulators are presented to show the results which indicate good position tracking performance and robustness against payload uncertainty and external disturbances.     

基于观测器的机械手神经网络自适应控制

提出了一种基于观测器的机械手神经网络自适应轨迹跟随控制器设计方法,这里机 械手的动力学非线性假设是未知的,并且假设机械手仅有关节角位置测量.文中采用一个线 性观测器重构机械手的关节角速度,用神经网络逼近修正的机械手动力学非线性,改进系统 的跟随性能.基于观测器的神经网络自适应控制器能够保证机械手角跟随误差和观测误差的 一致终结有界性以及神经网络权值的有界性,最后给出了机械手神经网络自适应控制器-观 测器设计的主要理论结果,并通过数字仿真验证了所提方法的性能.     

Observer-Based Adaptive Controller Design of Flexible Manipulators Using Time-Delay Neuro-Fuzzy Networks

In this paper, a dynamical time-delay neuro-fuzzy controller is proposed for the adaptive control of a flexible manipulator. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity. For a perfect tracking control of the robot, the output redefinition approach is used in the adaptive controller design using time-delay neuro-fuzzy networks. The time-delay neuro-fuzzy networks with the rule representation of the TSK type fuzzy system have better learning ability for complex dynamics as compared with existing neural networks. The novel control structure and learning algorithm are given, and a simulation for the trajectory tracking of a flexible manipulator illustrates the control performance of the proposed control approach.     

Adaptive output feedback tracking control of robot manipulators using position measurements only

In this paper, a new adaptive neuro controller for trajectory tracking is developed for robot manipulators without velocity measurements, taking into account the actuator constraints. The controller is based on structural knowledge of the dynamics of the robot and measurements of joint positions only. The system uncertainty, which may include payload variation, unknown nonlinearities and torque disturbances is estimated by a Chebyshev neural network (CNN). The adaptive controller represents an amalgamation of a filtering technique to generate pseudo filtered tracking error signals (for the elimination of velocity measurements) and the theory of function approximation using CNN. The proposed controller ensures the local asymptotic stability and the convergence of the position error to zero. The proposed controller is robust not only to structured uncertainty such as payload variation but also to unstructured one such as disturbances. Moreover the computational complexity of the proposed controller is reduced as compared to the multilayered neural network controller. The validity of the control scheme is shown by simulation results of a two-link robot manipulator. Simulation results are also provided to compare the proposed controller with a controller where velocity is estimated by finite difference methods using position measurements only.     

Robustness improvement of a nonlinear H∞ controller for robot manipulators via saturation functions

In this paper, previous works on nonlinear H_∞ control for robot manipulators are extended. In particular, integral terms are considered to cope with persistent disturbances, such as constant load at the end‐effector. The extended controller may be understood as a computed‐torque control with an external PID, whose gain matrices vary with the position and velocity of the robot joints. In addition, in order to increase the controller robustness, an extension of the algorithms with saturation functions has been carried out. This extension deals with the resulting nonlinear equation of the closed‐loop error. A modified expression for the required increment in the control signal is provided, and the local closed‐loop stability of this approach is discussed. Finally, simulation results for a two‐link robot and experimental results for an industrial robot are presented. The results obtained with this technique have been compared with those attained with the original controllers to show the improvements achieved by means of the proposed method. © 2005 Wiley Periodicals, Inc.     

仿人机器人控制系统研究及其关节控制器设计

论述了由嵌入式计算机组成的3层仿人机器人控制系统,并详细介绍了其中的关节控制器。控制系统实行逐级控制,任务分散,提高了机器人的智能化程度。关节控制器选用TM320F2811型数字信号处理器作为处理器,具有全数字型、集成度高、体积小、功耗低、可实现多轴运动控制的特点。关节控制策略采用模糊PD结合传统PI调节的算法,实验结果表明这种控制算法具有较强快速性、精确性、鲁棒性。     

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．     

Adaptive control of redundant multiple robots in cooperative motion

A redundant robot has more degrees of freedom than what is needed to uniquely position the robot end-effector. In practical applications the extra degrees of freedom increase the orientation and reach of the robot. Also the load carrying capacity of a single robot can be increased by cooperative manipulation of the load by two or more robots. In this paper, we develop an adaptive control scheme for kinematically redundant multiple robots in cooperative motion.In a usual robotic task, only the end-effector position trajectory is specified. The joint position trajectory will therefore be unknown for a redundant multi-robot system and it must be selected from a self-motion manifold for a specified end-effector or load motion. In this paper, it is shown that the adaptive control of cooperative multiple redundant robots can be addressed as a reference velocity tracking problem in the joint space. A stable adaptive velocity control law is derived. This controller ensures the bounded estimation of the unknown dynamic parameters of the robots and the load, the exponential convergence to zero of the velocity tracking errors, and the boundedness of the internal forces. The individual robot joint motions are shown to be stable by decomposing the joint coordinates into two variables, one which is homeomorphic to the load coordinates, the other to the coordinates of the self-motion manifold. The dynamics on the self-motion manifold are directly shown to be related to the concept of zero-dynamics. It is shown that if the reference joint trajectory is selected to optimize a certain type of objective functions, then stable dynamics on the self-motion manifold result. The overall stability of the joint positions is established from the stability of two cascaded dynamic systems involving the two decomposed coordinates.     

Manipulator motion control in operational space using joint velocity inner loops

This paper addresses the operational space motion control—trajectory tracking—of robot manipulators endowed with joint velocity feedback inner loops. A general structure for model-based joint velocity controllers is proposed for the inner loop. The required joint velocity reference is provided by an outer loop inspired from the robot kinematic control approach. It is shown that above two-loops control schemes lead to a nice cascade structure for the corresponding closed-loop systems. A stability result adapted for analysis of this particular kind of systems is developed in the paper; sufficient conditions for global exponential stability of this class of cascade systems are obtained. The effectiveness of the proposed control approach is evaluated on a direct-drive mechanical arm, and compared with a typical control strategy based on inverse kinematics resolution for computation of the desired motion in joint space, and the use of the computed-torque technique. The experimental evidences show better performance of the proposed two-loops controller.     

Experimental Testing of a Gauge Based Collision Detection Mechanism for a New Three‐Degree‐of‐Freedom Flexible Robot

The use of flexible robots can be easily justified in two main cases: (1) when the weight of the robot has to be minimized and (2) when collisions between the robot and the environment are foreseen, since a flexible, lightweight robot implies less impact energy. The position control of these robots has already been analyzed in previous communications. However, the second of these cases justifying the use of flexible robots requires further consideration, leading to the development of a force controller. Inmost up to date analysis the force control is studied beginning from a known contact point at a given collision time. In a more realistic approach, however, an accurate detection of the collision would be needed prior to dealing with the force control. After developing a reliable position controller for a three‐degree‐of‐freedom flexible robot using strain gauges placed over the robot structure, in this paper we deal with the possibility of carrying out the collision detection for the same prototype. This has been easily achieved by analyzing some estimated signals such as tip position and tip velocity. However, a complete analysis of the information obtained with the sensors has been required to obtain those estimates and a signal processing scheme had to be devised for a previous filtering of the original signals from the sensors (encoders and strain gauges). This work has been carried out as a first step towards the position/force control. Experimental results on a three‐degree‐of‐freedom flexible arm prototype are presented to verify how well this method performs. © 2003 Wiley Periodicals, Inc.