Constrained motion control of flexible robot manipulators based on recurrent neural networks

In this paper, a neural network approach is presented for the motion control of constrained flexible manipulators, where both the contact force everted by the flexible manipulator and the position of the end-effector contacting with a surface are controlled. The dynamic equations for vibration of flexible link and constrained force are derived. The developed control, scheme can adaptively estimate the underlying dynamics of the manipulator using recurrent neural networks (RNNs). Based on the error dynamics of a feedback controller, a learning rule for updating the connection weights of the adaptive RNN model is obtained. Local stability properties of the control system are discussed. Simulation results are elaborated on for both position and force trajectory tracking tasks in the presence of varying parameters and unknown dynamics, which show that the designed controller performs remarkably well.     

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 control of robot manipulators with flexible joints

Presents an adaptive control scheme for flexible joint robot manipulators. Asymptotic stability is insured regardless of the joint flexibility value, i.e., the results are not restricted to weak joint elasticity. Moreover, the joint flexibility is not assumed to be known. Joint position and velocity tracking errors are shown to converge to zero with all the signals in the system remaining bounded     

Tracking control of a flexible robot link

The formulation of an appropriate hybrid lumped/distributed model of a flexible robot link makes it possible to formulate and study tracking problems without the necessity for a priori approximations in the flexibility model for the link. The use of secondary support beam and active tip control provides perfect tracking with hypothetical exact measurements, and tracking to arbitrary accuracy with use of a variant of the acceleration feedback technique     

Force/motion control of constrained manipulators without velocitymeasurements

In this paper the authors deal with the problem of force/tracking control of constrained manipulators without velocity measurements interacting with an infinitely stiff environment. They use a reduced-order model for which the coordinate space is restricted to a subset R where the Jacobian constraint is guaranteed to be nonsingular. In contrast to other similar approaches, the authors do not assume that the generalized trajectories belong to the subset Ω all the time, thus our contribution is to prove that if the trajectories start within the subset Ω they remain in it. Furthermore, we prove uniform asymptotic stability considering only position and force measurements     

An adaptive fuzzy strategy for motion control of robot manipulators

This paper makes an attempt to develop a self-tuned proportional-integral-derivative (PID)-type fuzzy controller for the motion control of robot manipulators. In recent past, it has been widely believed that static fuzzy controllers can not be suitably applied for controlling manipulators with satisfaction because the robot manipulator dynamics is too complicated. Hence more complicated and sophisticated neuro-fuzzy controllers and fuzzy versions of nonlinear controllers have been more and more applied in this problem domain. The present paper attempts to look back at this widely accepted idea and tries to develop a self-tuned fuzzy controller with small incremental complexity over conventional fuzzy controllers, which can yet attain satisfactory performance. The proposed controller is successfully applied in simulation to control two-link and three-link robot manipulators.     

Adaptive control of flexible link manipulators using a pseudolink dynamic model

This paper presents a novel adaptive control scheme for a lightweight manipulator arm governed by electric motors. The controller design is based on the dynamic model of the arm in a quasi-static approximation which consists of the transports subsystem and the motor equations corrected for the elastic compliance of the plant. A passivity property of the flexible electromechanical system is established and an adaptive motor controller is developed which contains the rigid manipulator controller as a part. The motor controller updates all unknown rigid manipulator parameters as well as elastic parameters and ensures global asymptotic stability of the tracking errors with all signals in the system remaining bounded. Projecting of parameter estimates is used in the update law to avoid possible singularities when generating control input. Simulation results for a single-link elastic arm confirm the validity and demonstrate advantages of the proposed method.     

Control of constrained manipulators with flexible joints

This paper presents results on control design of constrained manipulators with flexible joints. It will be assumed that such manipulators are under gravity and contact reaction effects. It is also assumed that measurable joint variables are limited to rotor angles and its velocities. A simple biased proportional and derivative feedback controller is shown to be able to drive the manipulator to a desired configuration specified in link angles with desired contact force specified in the direction normal to the constraint surface at the desired position. A sufficient condition for global stability will be established by using a Lyapunov function which is constructed taking into account the spring stiffness, gravity factors and constraint functions. An example is studied and computer simulation results are presented to show closed-loop performance. Editor: M. Corless     

Artificial potential method for control of constrained robot motion

The artificial potential method of constrained robot control is presented. The method does not imply knowledge of a detailed robot model and, nevertheless, makes it possible to drive a robot in the environment with obstacles of any shape and along a desired trajectory as well as to take into account constructive constraints. The method is based on the construction of an artificial potential that provides the absence of intermediate equilibriums in which the robot can be locked.     

An extremum-seeking control approach for constrained robotic motion tasks

In this paper, we propose two adaptive control schemes for multiple-input systems for execution of robot end-effector movements in the presence of parametric system uncertainties. The design of these schemes is based on Model Reference Adaptive Control (MRAC) while the adaptation of the controller parameters is achieved by Extremum Seeking Control (ESC). The two control schemes, which are called Multiple-Input ESC–MRAC and Multiple-Input Adaptive-Dynamic-Inversion ESC–MRAC, are suitable for linear and nonlinear systems respectively. Lyapunov and averaging analysis shows that the proposed schemes achieve practical asymptotic reference state tracking. The proposed methods are evaluated in simulations and in a real-world robotic experiment.     

Adaptive motion control design of robot manipulators: an input-output approach

An input-output approach to adaptive motion control design of robot manipulators is presented. The main technical device in our approach is the passivity theory. This formulation provides a framework suitable for the design of new control and adaptation laws. A new control law which consists of a computed torque part and a feedforward compensation part is analysed using this approach.     

Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators

A new robust neuro-fuzzy controller for autonomous and intelligent robot manipulators in dynamic and partially known environments containing moving obstacles is presented. The navigation is based on a fuzzy technique for the idea of artificial potential fields (APFs) using analytic harmonic functions. Unlike the fuzzy technique, the development of APFs is computationally intensive. A computationally efficient processing scheme for fuzzy navigation to reasoning about obstacle avoidance using APF is described, namely, the intelligent dynamic motion planning. An integration of a robust controller and a modified Elman neural networks (MENNs) approximation-based computed-torque controller is proposed to deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamics of the robot arm. The MENN weights are tuned online, with no off-line learning phase required. The stability of the overall closed-loop system, composed by the nonlinear robot dynamics and the robust neuro-fuzzy controller, is guaranteed by the Lyapunov theory. The purpose of the robust neuro-fuzzy controller is to generate the commands for the servo-systems of the robot so it may choose its way to its goal autonomously, while reacting in real-time to unexpected events. The proposed scheme has been successfully tested. The controller also demonstrates remarkable performance in adaptation to changes in manipulator dynamics. Sensor-based motion control is an essential feature for dealing with model uncertainties and unexpected obstacles in real-time world systems.     

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.     

Stability analysis of a robust PD control law for robot manipulators

The purpose of this article is to examine the stability of a robust and decentralized PD control law for robot manipulator control. The control law, which was developed by the authors, has been shown experimentally to be extremely simple to implement and highly accurate for position and force tracking in the presence of robot model uncertainty and payload variation. However, stability analysis has been difficult due to the nonlinearity of robot dynamics and the use of time-delayed measurements of joint torques and joint accelerations in the control law. A rigorous stability analysis is presented in this article using Popov's hyperstability theory. A sufficient condition for global stability is obtained that supports previous theoretical and experimental results. © 1996 John Wiley & Sons, Inc.     

Nonlinear torque control of a single‐link flexible robot

In this research, a nonlinear torque control law with a free function is applied to the simultaneous motion and vibration control of a single‐link flexible robot. A rigorous proof of the asymptotic stability of the closed‐loop system is provided and experiments are conducted by taking the free function in the feedback law as the output of one of the following vibration sensors: strain, shear force, reaction force, tip acceleration, and acceleration at some intermediate point. The experimental results demonstrate that the use of strain, shear force, and reaction force information in the control law can substantially suppress vibrations in the arm, while the effect of incorporating the acceleration information can be better or worse, depending on where the accelerometer is placed. ©1999 John Wiley & Sons, Inc.     

Flexible control for robot manipulators

We designed, implemented, and tested a real-time flexible controller for manipulating different types of robots and control algorithms. The robot-independent, IBM PC-based multiprocessor system contains a DSP56001 master controller, six independent HCTL-1100 joint processors for accurate robotic joint control, and an interface computer board for processor communication. The joint processors operate in four user-defined modes and can be connected directly to an incremental optical encoder, which accommodates specialized applications and eliminates extra hardware     

Finite-time control for robot manipulators

Finite-time control of the robot system is studied through both state feedback and dynamic output feedback control. The effectiveness of the proposed approach is illustrated by both theoretical analysis and computer simulation. In addition to offering an alternative approach for improving the design of the robot regulator, this research also extends the study of the finite-time control problem from second-order systems to a large class of higher order nonlinear systems.     

Modeling and control of two constrained manipulators

The coordinated control of two manipulators in the presence of environment constraints is studied in this paper. Such a control method is needed in applications in which the two manipulators grasp a common object whose motion is constrained by environments. The two manipulators are not only constrained with each other, but also constrained by the environment in their workspace. It is realized that the motion and constraint equations obtained directly from mechanics are not suitable for the control purpose. A set of equivalent equations are derived, which are in the standard form of the nonlinear system representation with clear state equations and output equations. A nonlinear feedback is found which exactly linearizes and decouples the dynamic nonlinear system of the two constrained manipulators. The coordinated controller design is then carried out based on the linearized system by using linear system theory.     

On generating the motion of industrial robot manipulators

In this study, an intelligent search algorithm is proposed to define the path that leads to the desired position and orientation of an industrial robot׳s manipulator end effector. The search algorithm gradually approaches the desired configuration by selecting and evaluating a number of alternative robot׳s configurations. A grid of the robot׳s alternative configurations is constructed using a set of parameters which are reducing the search space to minimize the computational time. In the evaluation of the alternatives, multiple criteria are used in order for the different requirements to be fulfilled. The alternative configurations are generated with emphasis being given to the robot׳s joints that mainly affect the position of the end effector. Grid resolution and size parameters are set on the basis of the desired output. High resolution is used for a smooth path and lower for a rough estimation, by providing only a number of the intermediate points to the goal position. The path derived is a series of robot configurations. This method provides an inexperienced robot programmer with flexibility to generate automatically a robotic path that would fulfill the desired criteria without having to record intermediate points to the goal position.     

Adaptive motion control of robot manipulators: A unified approach based on passivity

This paper presents a unified approach to direct adaptive motion control laws for robot manipulators that have been studied during the last few years by several authors. It provides a general approach based on sensivity to demonstrate the global asymptotic stability of adaptive schemes applied to rigid multilinked manipulators. It is shown that most of the schemes fit within this framework, which presents the advantage of being more systematic than other techniques and therefore will enable a unified presentation of the several schemes proposed to date and will increase our understanding of adaptive control of robot manipulators.