An adaptive link position tracking controller for rigid-linkflexible-joint robots without velocity measurements

This paper presents an adaptive partial state feedback controller for rigid-link flexible-joint (RLFJ) robots. The controller compensates for parametric uncertainty throughout the entire mechanical system while only requiring measurement of link position and actuator position. To eliminate the need for measuring link velocity and actuator velocity a set of filters is utilized as a surrogate for the unmeasurable quantities. Based on this set of filters, an adaptive integrator backstepping procedure is used to develop a torque input controller which guarantees semiglobal asymptotic link position tracking while also ensuring that all signals remain bounded during closed-loop operation. Simulation results for a two-link RLFJ robot are utilized to validate the performance of the proposed controller.     

Global Output Tracking Control of Flexible Joint Robots via Factorization of the Manipulator Mass Matrix

This paper investigates the problem of global output feedback tracking control of flexible joint robots. Despite the fact that only link position and actuator position are available from measurements, the proposed controller ensures that the link position globally tracks the desired trajectory while keeping all the remaining signals bounded. The controller development uses a partial state-feedback linearization technique combined with the integrator backstepping control design method whereas a filter and an observer are utilized to remove the requirement of link and actuator velocity measurements. Partial state-feedback linearization of robot dynamics is performed by factoring the manipulator mass matrix into a quadratic form involving an integrable root matrix. The applicability of the proposed general design methodology is illustrated by an example of flexible joint planar robots. Numerical results for a two-link flexible joint planar robot are also provided.      

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.     

Adaptive Output Feedback Control of Flexible-Joint Robots Using Neural Networks: Dynamic Surface Design Approach

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.     

A Saturating Extension of an Output Feedback Controller for Internally Damped Euler‐Lagrange Systems

In this research, a novel extension of the passivity‐based output feedback trajectory tracking controller is developed for internally damped Euler‐Lagrange systems with input saturation. Compared with the previous output feedback controllers, this new design of a combined adaptive controller‐observer system will reduce the risk of actuator saturation effectively via generalized saturation functions. Semi‐global uniform ultimate boundedness stability of the tracking errors and state estimation errors is guaranteed by Lyapunov stability analysis. An application of the proposed saturated output feedback controller is the stabilization of a nonholonomic wheeled mobile robot with saturated actuators towards desired trajectories. Simulation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.     

Noncertainty equivalent adaptive control of robot manipulators without velocity measurements

This paper presents a noncertainty equivalent adaptive motion control scheme for robot manipulators in the absence of link velocity measurements. A new output feedback adaptation algorithm, based on the attractive manifold design approach, is developed. A proportional-integral adaptation is selected for the adaptive parameter estimator to strengthen the passivity of the system. In order to relieve velocity measurements, an observer is designed to estimate the velocities. The controller guarantees semiglobal asymptotic motion tracking and velocity estimation, as well as L_∞ and L₂ bounded parameter estimation error. The effectiveness of the proposed controller is verified by simulations for a two-link robot manipulator and a four-bar linkage. The results are further compared with the earlier certainty-equivalent adaptive partial and full state feedback controller to highlight potential closed-loop performance improvements.     

Decoupling and tracking control for elastic joint robots with coupled joint structure

The paper deals with the modeling, identification, and control of a flexible joint robot developed for medical applications at the German Aerospace Center (DLR). In order to design anthropomorphic kinematics, the robot uses a coupled joint structure realized by a differential gearbox, which however leads to strong mechanical couplings inside the coupled joints and must be taken into account. Therefore, a regulation MIMO state feedback controller based on modal analysis is developed for each coupled joint pair, which consists of full state feedback (motor position, link side torque, as well as their derivatives). Furthermore, in order to improve position accuracy and simultaneously keep good dynamic behavior of the MIMO state feedback controller, a cascaded tracking control scheme is proposed, based on the MIMO state feedback controller with additional feedforward terms (desired motor velocity, desired motor acceleration, derivative of the desired torque), which are computed in a computed torque controller and take the whole rigid body dynamics into account. Stability analysis is shown for the complete controlled robot. Finally, experimental results with the DLR medical robot are presented to validate the practical efficiency of the approaches.     

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.     

Robust adaptive control of a robotic manipulator including motor dynamics

An adaptive nonlinear control law that incorporates the manipulator dynamics as well as dynamics of the actuator is developed in this article. The proposed adaptive robust tracking controller requires position measurements only. The controller consists of two parts: a linear observer that generates an estimated error from the error on the joint position, together with a linear feedback controller that utilizes the estimated states. The second part is an adaptive controller that utilizes the feedback states from the linear observer to generate a control effort that takes into consideration the dynamic parameters variation of the robot and actuator. The closed loop system is locally stable in the Lyapunov sense. © 1998 John Wiley & Sons, Inc.     

Robust finite-time tracking control of nonholonomic mobile robots without velocity measurements

The problem of robust finite-time trajectory tracking of nonholonomic mobile robots with unmeasurable velocities is studied. The contributions of the paper are that: first, in the case that the angular velocity of the mobile robot is unmeasurable, a composite controller including the observer-based partial state feedback control and the disturbance feed-forward compensation is designed, which guarantees that the tracking errors converge to zero in finite time. Second, if the linear velocity as well as the angular velocity of mobile robot is unmeasurable, with a stronger constraint, the finite-time trajectory tracking control of nonholonomic mobile robot is also addressed. Finally, the effectiveness of the proposed control laws is demonstrated by simulation.     

带扩展卡尔曼滤波的柔性关节机器人虚拟分解控制

针对柔性关节机器人在非完全状态反馈条件下的轨迹跟踪控制问题,本文提出一种基于虚拟分解控制(virtual decomposition control,VDC)理论和扩展卡尔曼滤波(extended Kalman filtering,EKF)观测的控制方法.首先,考虑模型参数的不确定性和外界扰动因素,分别设计刚性连杆子系统和柔性关节子系统的虚拟分解控制律.然后,为突破现有VDC方法依赖于全状态反馈测量的局限,设计一种基于EKF的间接状态观测器,实现了仅需电机侧位置和速度测量而不需连杆侧任何状态信息测量的闭环控制.此外,结合虚拟稳定和李雅普诺夫稳定理论给出了严格的系统稳定性证明.最后,实例对比仿真验证了所提出控制算法的有效性,且相比于基于传统拉格朗日整体动力学的典型算法,具有更优的轨迹跟踪性能.     

多自由度机械臂的饱和输出反馈有限时间同步位置控制EI北大核心CSCD

针对输入受限的多自由度机械臂高精度位置控制问题,本文充分考虑驱动器饱和非线性的影响,提出了多自由度机械臂输出反馈饱和有限时间比例–微分(PD)+同步位置控制策略,应用Lyapunov稳定性理论和几何齐次性技术证明了闭环系统的全局有限时间稳定性.非线性饱和函数的恰当引入,使得所提出的控制器具有清晰明确的上界,可以通过预先选择满足特定条件的控制器参数有效避免驱动器饱和问题;同步控制项的恰当引入,使得所提出的控制器兼顾了多自由度机械臂各轴间的同步协调性,从而获得更快的收敛速度和更好的系统整体性能,满足工程实际对机械臂的高精度要求.本文的数值仿真结果验证了所提出的控制方法的有效性和可行性.     

带执行器饱和的柔性关节机器人位置反馈动态面控制

针对带有执行器饱和的柔性关节机器人系统,提出一种位置反馈动态面控制,以实现机器人连杆的角位置跟踪.在一般动态面控制的设计框架下,设计观测器重构系统未知速度状态,利用径向基函数神经网络学习饱和非线性特性,结合“最小参数学习”算法减轻计算负担.通过Lyapunov方法证明得出闭环系统所有信号半全局一致有界,跟踪误差可以通过调节控制器参数达到任意小.仿真结果表明,控制系统能够克服外界干扰,有效补偿系统存在的执行器饱和,实现柔性关节机器人的准确跟踪控制.该方法避免了传统反演设计存在的“微分爆炸”现象,简化了设计过程.     

An adaptive partial state-feedback controller for RLED robotmanipulators

An adaptive partial state-feedback controller is designed for rigid-link electrically driven (RLED) robot manipulators. The controller is based on structural knowledge of the electromechanical dynamics of the RLED robot and measurements of link position and electrical winding current in each of the brushed DC link actuators. The proposed controller is designed to adapt for parametric uncertainty in the electromechanical dynamics while utilizing a dynamic filter to generate link velocity tracking error information. The controller, adaptation laws, and the pseudovelocity filter are designed via a Lyapunov-like approach, the benefit of which is that at the end of the design procedure the controller can be mathematically shown to produce semiglobal asymptotic link position tracking. The basic design approach can be extended to many types of multiphase motors     

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.     

Integration of saturated PI synchronous control and PD feedback for control of parallel manipulators

High-precision motion of parallel manipulators depends not only on the position accuracy of each actuator, but also on the position synchronization of all actuators. This paper presents a simple synchronized control algorithm for the setpoint position control of parallel manipulators, by incorporating cross-coupling technology into a common proportional-derivative (PD) control architecture. An integrated controller is developed, consisting of a PD control and a saturated proportional-integral (S-PI) control with feedback of the differential position errors amongst actuators (defined as the synchronization errors). The controller can stabilize the motion of each actuator, and meanwhile synchronize all actuators' motions so that both position and synchronization errors converge to zero. The control algorithm does not use the modeling parameters in the controller formulation, and thus permits easy implementation in practice. It is proved that the proposed method can guarantee global asymptotical stability of the system. Experiments conducted on a planar three-degree-of-freedom parallel manipulator demonstrate the effectiveness of the proposed approach.     

Adaptive sliding mode control for trajectory tracking of nonholonomic mobile robot with uncertain kinematics and dynamics

ABSTRACT

This article designs a novel adaptive trajectory tracking controller for nonholonomic wheeled mobile robot under kinematic and dynamic uncertainties. A new velocity controller, in which kinematic parameter is estimated, produces velocity command of the robot. The designed adaptive sliding mode dynamic controller incorporates an estimator term to compensate for the external disturbances and dynamic uncertainties and a feedback term to improve the closed-loop stability and account for the estimation error of external disturbances. The system stability is analyzed using Lyapunov theory. Computer simulations affirm the robustness of the designed control scheme.     

A globally stable state feedback controller for flexible joint robots

The paper addresses the problem of controlling the joints of a flexible joint robot with a state feedback controller and proposes a gradual way of extending such a controller towards the complete decoupling of the robot dynamics. The global asymptotic stability for the state feedback controller with gravity compensation is proven, followed by some theoretical remarks on its passivity properties. By proper parameterization, the proposed controller structure can implement a position, a stiffness or a torque controller. Experimental results on the DLR lightweight robots validate the method.     

Adaptive robust fuzzy control for path tracking of a wheeled mobile robot

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Adaptive Control of a Single Link Manipulator Including Motor and Input Unmodelled Dynamics

An adaptive nonlinear control law that incorporates the manipulatordynamics as well as dynamics of the actuator is developed in this article.The technique is based on nonlinear feedback linearization. The electricalparameters of the actuator are considered to be of uncertain values. Incontrast to known methods the robot position is the only measurementavailable, a nonlinear observer is designed to estimate the remaining statesrequired by the nonlinear controller. Moreover the input unmodelled dynamicsproblem is addressed in the context of nonlinear geometric designs.