Particle filtering based parameter estimation for systems with output-error type model structures

• Published in: Journal of the Franklin Institute Vol. 356; no. 10; pp. 5521 - 5540
• Main Authors: Ding, Jie, Chen, Jiazhong, Lin, Jinxing, Wan, Lijuan
• Format: Journal Article
• Language: English
• Published: Elmsford Elsevier Ltd 01.07.2019; Elsevier Science Ltd
• Subjects: Algorithms; Computer simulation; Conditional probability; Convergence; Error analysis; Innovations; Mathematical models; Nonlinear systems; Parameter estimation; Parameter identification; Probability density functions; Random sampling; Simulation

The output-error model structure is often used in practice and its identification is important for analysis of output-error type systems. This paper considers the parameter identification of linear and nonlinear output-error models. A particle filter which approximates the posterior probability dens...