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Parameter estimation for a dual-rate system with time delay.

Lei Chen1, Lili Han2, Biao Huang2

  • 1Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan University, Wuxi 214122, PR China; Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada AB T6G 2G6.

ISA Transactions
|February 11, 2014
PubMed
Summary
This summary is machine-generated.

This study presents a new method for estimating parameters and states in dual-rate systems with time delays. The approach uses a state augmentation method for efficient computation, validated by simulations and experiments.

Keywords:
Dual-rateKalman filterLeast squaresParameter estimationStochastic gradientTime delay

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Area of Science:

  • Control Systems Engineering
  • Signal Processing
  • System Identification

Background:

  • Dual-rate systems are common in various engineering applications, but their analysis is complicated by time delays.
  • Accurate parameter and state estimation is crucial for effective control and monitoring of these systems.
  • Existing methods for dual-rate systems with time delays can be computationally intensive.

Purpose of the Study:

  • To develop an efficient algorithm for simultaneous parameter and state estimation in dual-rate systems with time delays.
  • To reduce the computational load compared to conventional state estimation techniques.
  • To validate the proposed algorithm through simulations and experimental studies.

Main Methods:

  • Derivation of a slow-rate model for the dual-rate system with time delay using discretization.
  • Simultaneous estimation of system parameters and states.
  • Kalman filter application for state estimation.
  • Stochastic gradient or recursive least squares algorithms for parameter estimation.
  • State augmentation method for reduced computational complexity in state estimation.

Main Results:

  • Successful simultaneous estimation of parameters and states in the dual-rate system with time delay.
  • The state augmentation method demonstrated a lower computational load compared to traditional approaches.
  • Simulation results and experimental data confirmed the effectiveness of the proposed algorithm.

Conclusions:

  • The proposed method provides an efficient and effective solution for parameter and state estimation in dual-rate systems with time delays.
  • The state augmentation technique offers significant computational advantages.
  • The algorithm is validated and suitable for practical applications.