An Algorithm for Robust Tracking Control of Robots

Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Zoran R. Novaković ◽  
Leon Z˘lajpah

SUMMARYBased on the Lyapunov theory, a new principle was developed for synthesizing robot tracking control in the presence of model uncertainties. First, a general Lyapunov-like robust tracking concept is presented. It is then used as a basis for the control algorithm derived via a quadratic Lyapunov function constructed using a sliding mode function (based on the output error). Control synthesis is made in task-space, without any need for solving the inverse kinematics problem, i.e. one does not need to inver the Jacobian matrix. It is also shown that the tracking error becomes close to zero in a settling time which is less than a prescribed finite time. Simulation results are incorporated.

2015 ◽  
Vol 15 (1) ◽  
pp. 34-45
Author(s):  
Sanxiu Wang ◽  
Kexin Xing ◽  
Zhengchu Wang

Abstract In this paper an adaptive fuzzy H∞ robust tracking control scheme is developed for a class of uncertain nonlinear Multi-Input and Multi-Output (MIMO) systems. Firstly, fuzzy logic systems are introduced to approximate the unknown nonlinear function of the system by an adaptive algorithm. Next, a H∞ robust compensator controller is employed to eliminate the effect of the approximation error and external disturbances. Consequently, a fuzzy adaptive robust controller is proposed, such that the tracking error of the resulting closed-loop system converges to zero and the tracking robustness performance can be guaranteed. The simulation results performed on a two-link robotic manipulator demonstrate the validity of the proposed control scheme.


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