Identification of time-varying pH processes using sinusoidal signals

DOI10.1016/j.automatica.2004.11.003zbMath1061.93525OpenAlexW1994908593MaRDI QIDQ1776421

Liuping Wang, Alex D. Kalafatis, William R. Cluett

Publication date: 12 May 2005

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2004.11.003

zbMATH Keywords

Nonlinear systemsWiener modelTime-varying systemspH controlRecursive least squaresOn-line identification

Mathematics Subject Classification ID

System identification (93B30) Application models in control theory (93C95)

Related Items (9)

Instrumental variables approach to identification of a class of MIMO Wiener systems ⋮ A unified approach for the parametric identification of SISO/MIMO Wiener and Hammerstein systems ⋮ The bias compensation based parameter and state estimation for observability canonical state-space models with colored noise ⋮ Real‐time identification of nonlinear multiple‐input–multiple‐output systems with unknown input time delay using Wiener model with Neuro‐Laguerre structure ⋮ Adaptive discrete-time sliding-mode control of nonlinear systems described by Wiener models ⋮ A recursive parametric estimation algorithm of multivariable nonlinear systems described by Hammerstein mathematical models ⋮ Frequency Response Estimation from Impulse or Step-like Response by Virtual Experiments ⋮ Adaptive control of a Wiener type system: application of a pH Neutralization reactor ⋮ Control relevant identification for robust optimal control

Cites Work

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• Compensation of the RLS algorithm for output nonlinearities
• On estimation of errors caused by non-linear undermodelling in system identification
• Comparison of four gradient-learning algorithms for neural network Wiener models
• Recursive subspace identification of linear and nonlinear Wiener state-space models

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