Tych, Wlodzimierz and Sadeghi, Jafar and Smith, Paul James and Chotai, Arunkumar and Taylor, Charles James (2012) Multi-state dependent parameter model identification and estimation. In: System Identification, Environmental Modelling, and Control System Design. Springer, London, pp. 191-210. ISBN 9780857299734
Full text not available from this repository.Abstract
This chapter describes an important generalisation of the State Dependent Parameter (SDP) approach to the modelling of nonlinear dynamic systems to include Multi-State Dependent Parameter (MSDP) nonlinearities. The recursive estimation of the MSDP model parameters in a multivariable state space occurs along a multi-path trajectory, employing the Kalman Filter and Fixed Interval Smoothing algorithms. The novelty of the method lies in redefining the concepts of sequence (predecessor, successor), allowing for its use in a multi-state dependent context, so producing efficient parameterisation for a fairly wide class of non-linear, stochastic dynamic systems. The format of the estimated model allows its direct use in control system design. Two worked examples in Matlab are included.