Recursive estimation of the continuous-time process parameters

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


The problem of continuous-time process parameter identification is considered. Filtered input-output process signals are used to create a linear differential equation governed by the same continuous-time process parameters. The estimation scheme is implemented by sampling the filtered signals and using a recursive least squares algorithm (RLS). The choice of filter leads to different parameter convergence properties. Conditions for parameter convergence are established in terms of frequency content of the input signal. The convergence rate is also analysed and an upper bound on the parameter error norm is given. The relation between choice of filter, sampling time selection and quality of the estimates is discussed and exemplified with simulation examples.


  • Carlos Canudas de Wit
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering


  • Convergence, Differential equations, Frequency, Least squares approximation, Nonlinear filters, Parameter estimation, Recursive Estimation, Resonance light scattering, Signal processing, Signal sampling
Original languageEnglish
Title of host publication25th IEEE Conference on Decision and Control, 1986
Publication statusPublished - 1986
Publication categoryResearch
Event25th IEEE Conference on Decision and Control, 1986 - Athens, Greece
Duration: 1986 Dec 101986 Dec 12
Conference number: 25


Conference25th IEEE Conference on Decision and Control, 1986