Parameter Estimation With Partial Forgetting Method

The paper proposes a new estimating algorithm for linear parameter varying systems with slowly time-varying parameters when the rate of change of individual parameters is different. It introduces a true probability density function, describing ideally the behaviour of parameters. However, as it is unknown, we search for its best approximation. A convex combination of point estimates, defined by individual hypotheses about the true probability density function, is then approximated by a single density. That serves as the best available description of parameters’ behaviour and it is therefore suitable e.g. for prediction purposes.