Representation and identification of a nonlinear aeroelastic pitch-plunge system as a model of the Nonlinear AutoRegressive, Moving Average eXogenous (NARMAX) class is considered. A nonlinear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properti...

This paper describes the design of a new self-tuning controller to control tip trajectory and tip deflection of a two-link flexible manipulator handling variable payloads based on nonlinear autoregressive with moving average and exogenous input (NARMAX) model. This proposed adaptive controller consists of a multivariate proportional integral and derivative (PID) feedback loop. The gains of the ...

A nonlinear autoregressive moving average with exogenous input (NARMAX) model structure is used to develop paraplegic dynamic leg joint model and the result is compared to a model built using artificial neural network (ANN). A series of experiments employing Functional Electrical Stimulation (FES) with varying pulse width are conducted to determine the impact of the leg swing angle. The data ob...

The nonlinear autoregressive moving average with exogenous inputs (NARMAX) model provides a powerful representation for time series analysis, modeling and prediction due to its strength to accommodate the dynamic, complex and nonlinear nature of real time series applications. This paper focuses on the modeling and prediction of NARMAX-model-based time series using the fuzzy neural network (FNN)...

In this paper the orthogonal estimation algorithm is used to estimate a NARMAX model for an aircraft gas turbine. The performance of the model is validated using a range of small and large signal tests and by examining the model’s static and dynamic characteristics. The NARMAX representation allows the direct mapping to the frequency domain by computing the Higher Order Frequency Response Funct...

This paper presents an original approach for nonlinear Volterra and NARMAX filter identification. We propose here to use a non persistent excitation of input sequence to excite few terms of the Volterra and NARMAX filter, which must satisfy a set of physical constraints. Expressions have been developped to evaluate the accurate number of excited terms of the Volterra and NARMAX filter.

The approach to the design of direct current (DC) motor varies considerably using advanced methods such as artificial intelligence (AI). However, accuracy issues cannot be totally addressed using conventional methods. This paper presents the study on nonlinear autoregressive moving average with exogenous input (NARMAX) model using multilayer perceptron (MLP) neural network for DC motor modeling...

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It has been found that the response of acupuncture point on the human meridian line exhibits nonlinear dynamic behavior when excitation of electroacupuncture is implemented on another meridian point. This nonlinear phenomenon is in fact a hysteretic phenomenon. In order to explore the characteristic of human meridian and finally find a way to improve the treatment of diseases via electro-acupun...