Piezoelectric vibration suppression technology (PVST) utilizes the inverse piezoelectric
effect of piezoelectric materials to suppress the vibration of mechanisms through stress or …

This paper presents tailor-made neural model structures and two custom fitting criteria for
learning dynamical systems. The proposed framework is based on a representation of the …

A novel higher-order context-layered recurrent pi-sigma neural network (CLRPSNN) is
presented for the identification of nonlinear dynamical systems. The proposed model is the …

Controlling complex nonlinear dynamical systems using traditional methods has always
been a difficult task because the majority of systems seen in nature have intricate nonlinear …

In this brief, we develop data-based methods for analyzing the controllability and
observability of linear discrete-time systems which have unknown system parameters. These …

Au cours des deux dernières décennies, les performances des équipements industriels ont
considérablement été augmentées. L'intégration de calculateurs performants dans les …

In this paper, identification and control for a class of nonlinear systems with unknown
constant or variable control gains are investigated. By reformulating the original system …

A model-following adaptive control structure is proposed for the speed control of a nonlinear
motor drive system and the compensation of the nonlinearities. A recurrent artificial neural …

This paper proposes a nonlinear control approach using dynamic neural network-based
input–output feedback linearization to resolve the inherent conflicting performance criteria …

In recent years, with the development of machine vision and other relative techniques, visual
servoing control of robotics has been wildly applied. A complex calibration process is …