Perfect position/force tracking of robots with dynamical terminal sliding mode control

A Novel Prescribed-Performance-Tracking Control System with Finite-Time Convergence Stability for Uncertain Robotic Manipulators

Through this article, we present an advanced prescribed performance-tracking control system with finite-time convergence stability for uncertain robotic manipulators. It is therefore necessary to define a suitable performance function and error transformation to guarantee a prescribed performance within a finite time. Following the definitions mentioned, a modified integral nonlinear sliding-mode hyperplane is constructed from the transformed errors. By using the designed nonlinear sliding-mode surface and the super-twisting reaching control law, an advanced approach to the prescribed performance control was formed for the trajectory tracking control of uncertain robotic manipulators. The proposed controller exhibits improved properties, including estimated convergence speed and a predefined upper and lower limit for maximum overshoot during transient responses. Furthermore, the maximum allowable size of the control errors at the steady-state can be predefined and these errors will inevitably converge to zero within a finite time, while the proposed controller can provide a smooth control torque without the loss of its robustness. It is shown that the proposed control system is globally stable and convergent over a finite time. A comprehensive analysis of the effectiveness of the proposed control algorithm was already conducted via the simulation of an industrial robot manipulator.

Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone

In this paper, the adaptive neural network (NN) tracking control problem is addressed for robot manipulators subject to dead-zone input. The control objective is to design an adaptive NN controller to guarantee the stability of the systems and obtain good performance. Different from the existing results, which used NN to approximate the nonlinearities directly, NNs are employed to identify the originally designed virtual control signals with unknown nonlinear items in this paper. Moreover, a sequence of virtual control signals and real controller are designed. The adaptive backstepping control method and Lyapunov stability theory are used to prove the proposed controller can ensure all the signals in the systems are semiglobally uniformly ultimately bounded, and the output of the systems can track the reference signal closely. Finally, the proposed adaptive control strategy is applied to the Puma 560 robot manipulator to demonstrate its effectiveness.

Global finite-time adaptive control for uncalibrated robot manipulator based on visual servoing

The paper addresses the finite-time convergence problem of a uncalibrated camera-robot system with uncertainties. These uncertainties include camera extrinsic and intrinsic parameters, robot dynamics and feature depth parameters, which are all considered as time-varying uncertainties. In order to achieve a better dynamic stability performance of the camera-robot system, a novel FTS adaptive controller is presented to cope with rapid convergence problem. Meanwhile, FTS adaptive laws are proposed to handle these uncertainties which exist both in robot and in camera model. The finite-time stability analysis is discussed in accordance with homogeneous theory and Lyapunov function formalism. The control method we proposed extends the asymptotic stability results of visual servoing control to a finite-time stability. Simulation has been conducted to demonstrate the performance of the trajectory tracking errors convergence under control of the proposed method.