In this study, the control problem of complex robot system with uncertainties and
disturbances is addressed. Fuzzy system-fuzzy neural network-backstepping control (FS …

This paper addresses the problem of adaptive neural tracking control for nonlinear nonstrict-
feedback systems. The state variables are immeasurable and only the system output is …

This study develops an intelligent global sliding mode control using recurrent feature
selection neural network for active power filter (APF). First, the dynamic model of an APF is …

In this article, a self-organizing global sliding mode control (GSMC) is developed for a class
of dynamic systems, whereby modeling uncertainties are estimated by metacognitive fuzzy …

This article considers a robust intelligent control problem for a class of power-electronic
converters via a neuro-fuzzy learning mechanism. First, a terminal sliding-mode control …

This research is mainly concerned with the consensus tracking problem for a class of high-
order non-strict feedback nonlinear multi-agent systems, in which the virtual and the actual …

This study aims to develop a continuous terminal sliding mode control using meta-cognitive
fuzzy neural network for active power filter (APF). Different from conventional sliding mode …

This paper addresses neural adaptive quantized control for switched nonlinear non-strict
feedback systems. The systems under consideration have unknown virtual control …

In this article, a nonlinear adaptive fuzzy backstepping controller combined with an adaptive
backstepping controller and an adaptive fuzzy controller is proposed for real-time tracking …

The adaptive tracking control strategy is investigated for a class of multi-input and multi-
output pure-feedback nonlinear delayed systems with unknown dead-zone inputs. This …