Adaptive stabilization and tracking control of electrically driven manipulators

This article presents two new adaptive strategies for motion control of uncertain rigid-link, electrically driven manipulators. The first controller is a position regulation scheme that ensures (semiglobal) asymptotic convergence of the position error if no external disturbances are present, and convergence to an arbitrarily small neighborhood of zero in the presence of bounded disturbances. It is shown that the regulation scheme can be modified to provide accurate trajectory tracking control through the introduction of adaptive feedforward elements in the control law; this second control strategy retains the simple structure of the first controller and ensures arbitrarily accurate tracking in the presence of bounded disturbances. Each of the adaptive schemes is computationally efficient and requires virtually no information concerning either the manipulator or actuator models. Computer simulation results are given for a PUMA 560 manipulator and demonstrate that accurate and robust motion control can be achieved by using the proposed controllers. Experimental results are presented for an IMI Zebra Zero manipulator and confirm that the proposed approach provides a simple and effective means of obtaining high performance motion control. © 1996 John Wiley & Sons, Inc.     

Adaptive tracking control of rigid manipulators using only position measurements

This article presents a new approach to trajectory tracking control of uncertain rigid manipulators using only position measurements. The proposed control strategy is an adaptive scheme that is very general and computationally efficient, requires virtually no information regarding the manipulator dynamic model, and is implementable without calculation of the robot inverse dynamics or inverse kinematic transformations. It is shown that the controller ensures semiglobal uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Additionally, it is demonstrated that the proposed strategy can be used as the basis for developing controllers for “cascaded” robotic systems, such as manipulators with significant actuator dynamics or joint flexibility. The efficacy of this approach to manipulator control is illustrated through both computer simulations and hardware experiments. © 1997 John Wiley & Sons, Inc.     

Robust adaptive control of redundant manipulators

This paper presents an adaptive scheme for the motion control of kinematically redundant manipulators. The proposed controller is very general and computationally efficient since it does not require knowledge of either the mathematical model or the parameter values of the robot dynamics, and is implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategy is globally stable in the presence of bounded disturbances, and that in the absence of disturbances the size of the residual tracking errors can be made arbitrarily small. The performance of the controller is illustrated through computer simulations with a nine degree-of-freedom (DOF) compound manipulator consisting of a relatively small, fast six-DOF manipulator mounted on a large three-DOF positioning device. These simulations demonstrate that the proposed scheme provides accurate and robust trajectory tracking and, moreover, permits the available redundancy to be utilized so that a high bandwidth response can be achieved over a large workspace.     

Adaptive explicit force control of position-controlled manipulators

This article presents a new adaptive outer-loop approach for explicit force regulation of position-controlled robot manipulators. The strategy is computationally simple and does not require knowledge of the manipulator dynamic model, the inner-loop position controller parameters, or the environment. It is shown that the control strategy guarantees global uniform boundedness of all signals and convergence of the position/force regulation errors to zero when applied to the full nonlinear robot dynamic model. If bounded external disturbances are present, a slight modification to the control scheme ensures that global uniform boundedness of all signals is retained and that arbitrarily accurate stabilization of the regulation errors can be achieved. Additionally, it is shown that the adaptive controller is also applicable to robotic systems with PID inner-loop position controllers. Computer simulation results are given for a Robotics Research Corporation (RRC) Model K-1207 redundant arm and demonstrate that accurate and robust force control is achievable with the proposed controller. Experimental results are presented for the RRC Model K-1207 robot and confirm that the control scheme provides a simple and effective means of obtaining high-performance force control. © 1996 John Wiley & Sons, Inc.     

Decentralized adaptive control of manipulators

This article presents two new adaptive schemes for motion control of robot manipulators. The first controller possesses a partially decentralized structure in which the control input for each task variable is computed based on information concerning only that variable and on two “scaling factors” that depend on the other task variables. The need for these scaling factors is eliminated in the second controller by exploiting the underlying topology of the robot configuration space, and this refinement permits the development of a completely decentralized adaptive control strategy. The proposed controllers are computationally efficient, do not require knowledge of either the mathematical model or the parameter values of the robot dynamics, and are shown to be globally stable in the presence of bounded disturbances. Furthermore, the control strategies are general and can be implemented for either position regulation or trajectory tracking in joint-space or task-space. Computer simulation results are given for a PUMA 762 manipulator, and these demonstrate that accurate and robust trajectory tracking is achievable using the proposed controllers. Experimental results are presented for a PUMA 560 manipulator and confirm that the proposed schemes provide simple and effective real-time controllers for accomplishing high-performance trajectory tracking. © 1994 John Wiley & Sons, Inc.     

Adaptive tracking control of manipulators: Theory and experiments

This paper considers the trajectory tracking problem for uncertain robot manipulators and proposes two adaptive controllers as solutions to this problem. The first controller is derived under the assumption that the manipulator state is measurable, while the second strategy is developed for those applications in which only position measurements are available. The adaptive schemes are very general and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the manipulator dynamics, and are implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategies ensure uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Experimental results are presented for a PUMA 560 manipulator and demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed controllers.     

A fully adaptive decentralized control of robot manipulators

In this paper, we develop a fully adaptive decentralized controller of robot manipulators for trajectory tracking. With high-order and adaptive variable-structure compensations, the proposed scheme makes both position and velocity tracking errors of robot manipulators globally converge to zero asymptotically while allowing all signals in closed-loop systems to be bounded, even without any prior knowledge of robot manipulators. Thus this control scheme is claimed to be fully adaptive. Even when the proposed scheme is modified to avoid the possible chattering in actual implementations, the overall performance will remain appealing. Finally, numerical results are provided to verify the effectiveness of the proposed schemes at the end.     

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.     

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.     

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

A stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first‐order Takagi–Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed‐loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

A robust adaptive sliding-mode control for rigid robotic manipulators with arbitrary bounded input disturbances

In this paper, a robust adaptive sliding-mode control scheme for rigid robotic manipulators with arbitrary bounded input disturbances is proposed. It is shown that the prior knowledge on the upper bound of the norm of the input disturbance vector is not required in the sliding-mode controller design. An adaptive mechanism is introduced to estimate the upper bound of the norm of the input disturbance vector. The estimate is then used as a controller gain parameter to guarantee that the output tracking error asymptotically converges to zero and strong robustness with respect to bounded input disturbances can be obtained. A simulation example is given in support of the proposed control scheme.     

Decentralized robust adaptive control of nonlinear systems withunmodeled dynamics

The authors present a decentralized robust adaptive output feedback control scheme for a class of large-scale nonlinear systems of the output feedback canonical form with unmodeled dynamics. A modified dynamic signal is introduced for each subsystem to dominate the unmodeled dynamics and an adaptive nonlinear damping is used to counter the effects of the interconnections. It is shown that under certain assumptions, the proposed decentralized adaptive control scheme guarantees that all the signals in the closed-loop system are bounded in the presence of unmodeled dynamics, high-order interconnections and bounded disturbances. Furthermore, by choosing the design constants appropriately, the tracking error can be made arbitrarily small regardless of the interconnections, disturbances, and unmodeled dynamics in the system. An illustration example demonstrates the effectiveness of the proposed scheme     

随机激励下单杆柔性关节机械臂的建模与控制

机械系统如移动机器人、机械臂等在运动过程中通常会受到随机干扰.针对随机激励下单连杆柔性机械臂的数学建模和控制问题,目前还没有相关的研究.本文引入随机干扰,建立了一个具有未知参数的随机动力学模型.然后通过坐标变换,将该模型化成一个4阶系统.在此基础上,结合自适应理论,动态面方法和Lyapunov方法,设计了一种新的控制器.这种控制器有效地避免了传统方法中的过参数估计和复杂性爆炸的问题,同时可以保证跟踪误差在均方意义下任意小,且闭环系统的所有信号依概率有界.最后通过一个仿真例子验证了本文理论的有效性.     

Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Adaptive position/force control of robot manipulators withoutvelocity measurements: theory and experimentation

In this paper, we design an adaptive position/force controller for robot manipulators during constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. A filtering technique is utilized to produce a pseudo-velocity error signal and thus, eliminate the need for link velocity measurements. The control strategy provides semiglobal asymptotic tracking performance for the end-effector position and the interaction force between the constraint and the end-effector. An experimental implementation of the proposed controller on a two-link planar robot is also presented.     

一种基于操作空间的操作器分散自适应控制方法

本文提出了一种操作器分散自适应阻力控制方法．这种方法不要求知道操作器动态模型的结构和参数，采用分散控制的形式，可以对各自由度单独进行控制，因此计算简单有效，具有一定的容错能力，控制系统有较好的暂态性能，由于控制律以操作空间坐标形式描述，适合于具有冗余自由度的操作器的控制．计算机仿真表明了该方法的良好的控制效果     

Adaptive Task-Space Control of Flexible-Joint Manipulators

This paper considers the motion control and compliance control problemsfor uncertain rigid-link, flexible-joint manipulators, and presents newadaptive task-space controllers as solutions to these problems. The motioncontrol strategy is simple and computationally efficient, requires littleinformation concerning either the manipulator or actuator/transmissionmodels, and ensures uniform boundedness of all signals and arbitrarilyaccurate task-space trajectory tracking. The proposed compliant motioncontrollers include an adaptive impedance control scheme, which isappropriate for tasks in which the dynamic character of theend-effector/environment interaction must be controlled, and an adaptiveposition/force controller, which is useful for those applications thatrequire independent control of end-effector position and contact force. Thecompliance control strategies retain the simplicity and model independenceof the trajectory tracking scheme upon which they are based, and are shownto ensure uniform boundedness of all signals and arbitrarily accuraterealization of the given compliance control objectives. The capabilities ofthe proposed control strategies are illustrated through computer simulationswith a robot manipulator possessing very flexible joints.     

Adaptive neural network control of coordinated manipulators

In this article, adaptive neural network control of coordinated manipulators is considered in an effort to eliminate the time‐consuming and error prone dynamic modeling process which is necessary for the implementation of conventional adaptive control. After a concise dynamic model in the object coordinate space is developed for the coordinated manipulators, an adaptive neural network controller is presented by combining the techniques of neural network parameterization, adaptive control, and sliding mode control. It can be shown that the motion tracking errors converge to zero asymptotically whereas the internal force tracking error remains bounded and can be made arbitrarily small. Numerical simulations are conducted to show the effectiveness of the proposed method. ©1999 John Wiley & Sons, Inc.     

Decentralized adaptive output feedback design for large-scalenonlinear systems

In this paper, we present a global, decentralized adaptive design procedure for a class of large-scale nonlinear systems, which utilizes only local output feedback. The advocated scheme guarantees robustness to parametric and dynamic uncertainties in the interconnections and also rejects any bounded disturbances entering the system. The systems belonging to this class are those which can be transformed using a global diffeomorphism to the output feedback canonical form, where the interconnections are a function of subsystem outputs only. The uncertainties are assumed to be bounded by an unknown pth-order polynomial in the outputs. The resulting controller maintains global robustness and disturbance rejection properties. The output tracking error is shown to be bounded within a compact set, the size of which can be made arbitrarily small by appropriate choice of the control gains. For the case where the objective is regulation, global asymptotic regulation of all the states of the closed-loop system is achieved     

Direct adaptive control of robotic systems

This paper presents a new approach to adaptive motion control of an important class of robotic systems. The control schemes developed using this approach are very simple and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the robotic system dynamics. It is shown that the control strategies are globally stable in the presence of bounded disturbances, and that the size of the tracking errors can be made arbitrarily small. The proposed controllers are very general and are implementable with a wide variety of robotic systems, including both open- and closed-kinematic-chain manipulators. Computer simulation results are given for a seven degree-of-freedom (DOF) Robotics Research Corporation Model K-1607 arm. These results demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed schemes.