Neural network-based reduced-order modeling for nonlinear vertical sloshing with experimental validation

Adaptive Neural Network Method for Consensus Tracking of High-Order Mimo Nonlinear Multi-Agent Systems

This paper is concerned with the consensus tracking problem of high order MIMO nonlinear multi-agent systems. The agents must follow a leader node in presence of unknown dynamics and uncertain external disturbances. The communication network topology of agents is assumed to be a fixed undirected graph. A distributed adaptive control method is proposed to solve the consensus problem utilizing re...

Identifying Nonlinear Parameters for Reduced Order Models. Part II, Validation using Experimental Data

Assembling nonlinear dynamic models of structures is the goal of numerous research and development organizations. Such a predictive capability is required in the development of advanced, high-performance aircraft structures. Specifically, the ability to predict the response of complex structures to aero-acoustic loading has long been a United States Air Force goal. Sonic fatigue has plagued the...

Reduced Order Modeling of Nonlinear Control Systems

Discrete-Time Reduced Order Neural Observers for Uncertain Nonlinear Systems

This paper focusses on a novel discrete-time reduced order neural observer for nonlinear systems, which model is assumed to be unknown. This neural observer is robust in presence of external and internal uncertainties. The proposed scheme is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF)-based algorithm, using a parallel configu...

An Approach for Reduced Order Modeling of Nonlinear Power Systems

-In this paper we present an approach for the reduced order modeling of nonlinear power systems. We describe a combined symbolic-numeric methodology for a local model order reduction which is based on the theory of singularly perturbed systems. Since the properties of power systems are taken into account, we were able to define an easy to use formula which eliminates the necessity of engineerin...