Parameter estimation via second order sliding modes with application to thermal modelling in a high speed rotating machine

Sliding mode observers (SMOs) are a well-developed technique with applications in condition monitoring and fault diagnosis (CMFD). Design of a SMO requires a nominal mathematical model. If this and indeed many other observer methodologies are to be routinely implemented in industry, automated methods are required for nominal parameter measurement. In this paper an algorithm for estimation of linear time invariant model parameters is developed. The concept of a second order sliding mode is used to increase the number of parameters that can be estimated from each dynamical equation. The results are demonstrated with simulated data from the cooling system of a dry vacuum pump. The algorithm is shown to be useful in estimating nominal parameters for the observer. Results show that the SMO based estimation scheme is also useful for continuous CMFD in a vacuum pump cooling system where intermittent faults are possible.