Experimental methods used to determine the dynamic behaviour of helicopter structures can be broadly categorised as either ground testing methods or in-flight testing methods. A major limitation of ground testing is that dynamic properties determined from a grounded helicopter structure are usually significantly influenced by the boundary conditions. Therefore, it is desirable to carry out test...

This paper extends current theory on the identification and estimation of vector time series models to nonstationary processes. It examines the structure of dynamic simultaneous equations systems or ARMAX processes that start from a given set of initial conditions and evolve over a given, possibly infinite, future time horizon. The analysis proceeds by deriving the echelon canonical form for su...

The joint problem of the recursive estimation of an optimal predictor for the closed-loop system and the unbiased parameter estimation of an ARMAX plant model in closed-loop operation is considered. A special reparameterized optimal predictor for the closed-loop is introduced. This allows a parameter estimation algorithm for the plant model to be derived which is globally asymptotically stable ...

The RobotMODIC project run by the Universities of Essex and Sheffield investigates ways of quantitative description and accurate, transparent modelling of robot-environment interaction. Transparent, analysable models allow the evaluation of robot controllers with regard to issues such as stability, relevance of individual sensor perceptions for the control task at hand, and quantitative compari...

In this paper the techniques of evolutionary system identification are implemented in the parametric, time domain identification of a flexible robotic arm. More specifically, the (μ+λ) Evolution Strategy (ES) is used for the estimation of both ARMA and ARMAX models, by means of Prediction-Error method (PEM), capable to describe system’s dynamics in the absence or existence of an input data set,...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

This paper presents an improved on-line identification method of non-linear time-varying dynamic systems with linear and non-linear models . This method is based on Genetic algorithms with a new technique to simulate the behaviour of the gradient method without using the concept of derivatives. This method uses an on-line identification algorithm that begins by calculating what ARX model adapts...