Recep Burkan

Application of robust and adaptive control techniques to cooperative manipulation

This paper presents a study on application of adaptive and robust control methods to a cooperative manipulation system, which is developed for handling an object by two-link planar robot manipulators. Adaptive control algorithm ensures a parameter adaptation law satisfying the stability condition of uncertain systems. In designing robust control structure, contact and friction constraints for grasp and bearing conditions, structural flexibility or such similar factors as various unmodeled dynamics are considered as the uncertainties that determine the available values of control parameters. The novelty of results in the present paper is to define new control inputs using the parametric uncertainties and the Lyapunov-based theory of guaranteed stability of uncertain systems.

Upper bounding estimation for robustness to the parameter uncertainty in trajectory control of robot arm

Abstract In this paper, a new robust control law is presented for robot manipulators subjected to uncertainties. Stability of the system is established by the Lyapunov function, and a control law that guaranteed the system stability is derived as a result of analytical solution. Apart from previous studies, uncertainty bound is determined with the estimation law to control the system properly and the estimation law is written as an exponential function of robot kinematics, inertia parameters and tracking error. Due to asymptotic stability and increasing convergence rate, tracking performance for the case of transient and steady-state are increased.

Parameter estimation and upper bounding adaptation in adaptive-robust control approaches for trajectory control of robots

In this paper a new robust adaptive control law for n-link robot manipulators with parametic uncertainties is derived using the Lyapunov theory thus guaranteed the stability of an uncertain system. The novelty of the adaptive robust control algorithm is that manipulator parameters and adaptive upper bounding functions are estimated to control the system properly, and the adaptive robust control law is also updated as an exponential function of manipulator kinematics, inertia parameters and tracking errors. The proposed adaptive control input includes a parameter estimation law as an adaptive controller and an additional control input vector as a robust controller. The developed approach has the advantages of both adaptive and robust control laws, without their discolour tags.

Upper Bounding Estimation for Robustness to the Parameter Uncertainty with Trigonometric Function in Trajectory Control of Robot Arms

In this paper, a new robust control law is considered for controlling robot manipulators subjected to uncertainties. The control law is derived as a result of analytical solution from the Lyapunov function, thus stability of the uncertain system is guaranteed. Apart from previous studies, uncertainty bound and adaptation gain matrix are updated in time with the estimation law to control the system properly and uncertainty bound is determined using a trigonometric function of robot kinematics, inertia parameters and tracking error while adaptation gain matrix is determined using a trigonometric function of robot kinematics and tracking error. Application to a two-link robotic manipulator is presented and numerical simulations are included.

Variable Upper Bounding Approach for Adaptive-Robust Control in Robot Control

This paper presents a new adaptive-robust control law for robot manipulators with parametric uncertainty. Stability of the uncertain system has been guaranteed using the Lyapunov theory and the control law is derived by means of analytical approach. In this scheme, the manipulator parameters are determined with an estimation law, and both adaptive gain and additional control input are also updated as a function of the estimated value. The proposed adaptive control input includes a parameter estimation law as an adaptive controller and an additional control input vector as a robust controller. The developed approach has the advantages of both adaptive and robust control laws, and besides it eliminates the disadvantages of them.

Design of an adaptive control law using trigonometric functions for robot manipulators

In this study, a new approach of adaptive control law for controlling robot manipulators using the Lyapunov based theory is derived, thus the stability of an uncertain system is guaranteed. The control law includes a PD feed forward part and a full dynamics feed forward compensation part with the unknown manipulator and payload parameters. The novelty of the obtained result is that an adaptive control algorithm is developed using trigonometric functions depending on manipulator kinematics, inertia parameters and tracking error, and both system parameters and adaptation gain matrix are updated in time.

Modelling of a logarithmic parameter adaptation law for adaptive control of mechanical manipulators

In the paper, a new adaptive control law for controlling robot manipulators is derived based on the Lyapunov theory; trigonometric functions are used for the derivation of the parameter estimation law. In this note, we have derived a logarithmic parameter estimation law based on a previous paper, and the boundedness of tracking error has been shown.

Robust and adaptive control of three dimensional revolute-jointed cooperative manipulators for handling automation

This paper presents a study of the application of adaptive and robust control methods to a cooperative manipulation system which is developed for handling an object by three dimensional revolute-jointed manipulators. The adaptive control algorithm supports the parameter adaptive law that provides guaranteed stability for uncertain systems. In designing the robust control structure, contact and friction constraints for grasp and bearing conditions, structural flexibility or such similar factors as various unmodeled dynamics are considered as uncertainties that determine available values of control parameters. The novelty of results in the present paper is to define new control inputs using parametric uncertainties and the Lyapunov based theory of guaranteed stability of uncertain systems for handling objects in a spatial workspace.