Abstract
This paper proposed a robust finite-time tracking controller with adaptive neural networks for uncertain robotic manipulators without velocity measurements. A simple output feedback controller plus a nonlinear filter is designed to achieve satisfied performance, such as high accuracy, and fast response, which is more convenient and lower cost for robotic manipulators in practice. The adaptive neural networks with finite-time convergence are designed to compensate the uncertainties, which effectively further improve the robustness. The Lyapunov stability theory and geometric homogeneity technique are employed to prove the practical finite-time stability of the whole closed-loop system. Simulations on two-degree robotic manipulators show the effectiveness and robustness of the proposed control strategy.
Highlights
The finite-time stabilization of nonlinear systems is considered as a more popular control technique because of its fast transient, high accuracy and strong robustness [1], [2], so that the finite-time stabilization method has been quickly used in robotic manipulators, and several strategies have been proposed in these papers [3]–[11]
Hong et al [11] firstly solved the problem of finite-time control of robotic manipulators, and extended to a large class of higher order nonlinear systems
This paper solved the problem of robust finite-time control for uncertain robotic manipulators without velocity measurements
Summary
The finite-time stabilization of nonlinear systems is considered as a more popular control technique because of its fast transient, high accuracy and strong robustness [1], [2], so that the finite-time stabilization method has been quickly used in robotic manipulators, and several strategies have been proposed in these papers [3]–[11]. Hong et al [11] firstly solved the problem of finite-time control of robotic manipulators, and extended to a large class of higher order nonlinear systems. The finitetime control of nonlinear systems is quickly developing recently, such as [12]–[27]. Yu et al [27] proposed a finitetime command filtered backstepping approach for a class of n-order nonlinear systems. In many practical applications, the finite-time tracking is more desirable
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