An adaptive control is proposed for a class of nonlinear systems with unknown time-varying delays and a dead-zone input. Taking the dead-zone as a part of the system dynamics, the construction of the dead-zone inverse model is not needed and thus the characteristic parameters of the dead-zone are not necessarily known. Unknown time delays are handled by introducing improved Lyapunov-Krasovskii functions, where the requirements on the delayed functions/ control coefficients are further relaxed without the singularity problem. A novel high-order neural network with only a scalar weight parameter is developed to approximate unknown nonlinearities. The closed-loop system is proved to be semi-globally uniformly ultimately bounded (SGUUB). Experiments on a robotic servo system are provided to verify the reliability of the presented method.
|Translated title of the contribution||Neural Network Control of Nonlinear Time-delay System with Unknown Dead-Zone and Its Application to a Robotic Servo System|
|Title of host publication||Trends in Intelligent Robotics 13th FIRA Robot World Congress, FIRA 2010, Bangalore, India, September 15-17, 2010. Proceedings|
|Editors||Prahlad Vadakkepat, Jong-Hwan Kim, Norbert Jesse, Abdullah Al Mamun, Tan Kok Kiong, Jacky Baltes, John Anderson, Igor Verner, David Ahlgren|
|Publisher||Springer Berlin Heidelberg|
|Pages||338 - 345|
|Number of pages||8|
|Publication status||Published - 2010|