There is a growing interest in the modeling and control of model helicopters using nonlinear dynamic models and nonlinear control. Application of a new intelligent control approach called Brain Emotional Learning Based Intelligent Controller (BELBIC) to design autopilot for an autonomous helicopter is addressed in this paper. This controller is applied to a nonlinear model of a helicopter. This...

Nonlinear Time History (NTH) analysis is currently the most reliable method for estimating structural behavior. Considerable computational demand and complexity of this method may cause difficulty for its routine practical application. Based on the Methodology of Endurance Time (ET) method, it can estimate the nonlinear response of structures with a much lower computational cost. In this resear...

In this note we study the strong dynamic input-output decoupling problem for nonlinear systems. Using an algebraic theory for nonlinear control systems, we obtain for a dynamic input-output decouplable nonlinear system a compensator of minimal dimension that solves the decoupling problem. AMS Subject Classifications: 93C10, 93B50, 93C35.

This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The res...

When performing nonlinear system identification few tools exist for the a priori nonlinear model structure selection of the nonlinear system. This paper presents a possible approach as a first step towards selecting a nonlineAtr system model structure, based on using the results of Lyapunov exponents, Poincar~ maps and dimension techniques. The approach is illusUated by applying it to the Chua ...

In practical engineering, it is difficult to establish complex nonlinear dynamic equations based on theories of mechanics. Data-driven models are built using neural networks in this paper meet the needs high dimension, multi-scale and precision. We construct a two-coefficient loss function for whole data-driven modeling substructure according linear multi-step method. The forward Euler method c...

We analyze a zero-sum stochastic differential game between two competing players who can choose unbounded controls. The payoffs of the game are defined through backward stochastic differential equations. We prove that each player’s priority value satisfies a weak dynamic programming principle and thus solves the associated fully non-linear partial differential equation in the viscosity sense.

Recent investigations have shown that the influences of Soil-Structure Interaction (SSI) may be detrimental to the seismic response of structure, and hence neglecting this phenomenon in analysis and design may lead to an un-conservative design. The objective of this paper is to quantify the effects of nonlinear soil-structure interaction on the seismic response of a low-rise special moment fram...

In order to expand a formal linearization method on designing an observer for nonlinear dynamic and measurement systems, we exploit the discrete Fourier expansion that can reduce computational complexity. A nonlinear multidimensional dynamic system is considered by a nonlinear ordinary differential equation, and a measurement equation is done by a nonlinear equation. Defining a linearization fu...