Advances in modelling, system identification and parameter estimation

System Identification and Parameter Estimation (191131700)

Piecewise modelling and parameter estimation of repairable system failure rate

Lifetime failure data usually presents a bathtub-shaped failure rate, and random failure phase dominates its life cycle. Relatively large errors always existed when single distribution model is used for analysis and modelling. Therefore, a bathtub-shaped reliability model based on piecewise intensity function was proposed for repairable system. Parameter estimation was studied by using maximum ...

Advances and selected recent developments in state and parameter estimation

This paper deals with two topics from state and parameter estimation. The first contribution of this work provides an overview of techniques used for determining which parameters of a model should be estimated. This is a question that commonly arises when fundamental models are used as these models often contain more parameters than can be reliably estimated from data. The decision of which par...

Advances in Parameter Estimation and Performance Improvement in Adaptive Control

In most adaptive control algorithms, parameter estimate errors are not guaranteed to converge to zero. This lack of convergence adversely affects the global performance of the algorithms. The effect is more pronounced in control problems where the desired reference setpoint or trajectory depends on the system's unknown parameters. This paper presents a parameter estimation routine that allows e...

Estimation of Modelling Errors in Structural System Identification

The study presented in this paper builds upon previous research into system identification using multiple models at EPFL. This identification methodology is based on the selection of sets of candidate models such that differences between measurements and their predictions are below a certain threshold value. The threshold value is a function of modeling and measurement errors. This paper presen...