Auxiliary Model‐Based Maximum Likelihood Multi‐Innovation Forgetting Gradient Identification for a Class of Multivariable Systems

Optimal Control Applications and Methods, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 29, 2025

ABSTRACT Through dividing a multivariable system into several subsystems, this paper derives the sub‐identification model. Utilizing obtained model, an auxiliary model‐based maximum likelihood forgetting gradient algorithm is derived. Considering enhancing parameter estimation accuracy, multi‐innovation (AM‐ML‐MIFG) proposed taking advantage of identification theory. Simulation results test effectiveness algorithms, and confirm that AM‐ML‐MIFG has satisfactory performance in capturing dynamic properties system.

Language: Английский

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Hierarchical Least Squares Identification for the Multivariate Input Nonlinear Controlled Autoregressive Moving Average Systems

International Journal of Adaptive Control and Signal Processing, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

ABSTRACT This article presents a decomposition‐based least squares estimation algorithm for the multivariate input nonlinear system. By using hierarchical identification principle, breaks down system into two subsystems, one containing parameters of linear dynamic block and other static block. Treating unknown variables contained in information vector model is to replace them with outputs an auxiliary model. The comparative results between recursive developed this are provided test proposed algorithms have lower computational cost higher accuracy. Furthermore, convergence analyzed, which can guarantee stability algorithm. simulation confirm efficacy derived effectively estimating systems.

Language: Английский

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Separable synchronous auxiliary model hybrid predictive gradient identification for nonlinear models based on the data preprocessing

Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Identification for Precision Mechatronics: An Auxiliary Model‐Based Hierarchical Refined Instrumental Variable Algorithm

International Journal of Robust and Nonlinear Control, Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

ABSTRACT When the physical properties of mechanical systems align with structure model, continuous‐time (CT) can be effectively represented by an interpretable and parsimonious additive formal models. This article addresses parameter estimation challenges CT autoregressive moving average (ACTARMA) systems. Based on maximum likelihood principle, optimality conditions for proposed identification algorithms are formulated ACTARMA Additionally, auxiliary model‐based hierarchical refined instrumental variable (AM‐HRIV) iterative algorithm AM‐HRIV recursive developed means principle model idea. These establish a pseudo‐linear regression relationship involving optimal prefilters derived from unified model. The effectiveness methods is demonstrated numerical simulation, performance method in identifying modal representations verified experimental data.

Language: Английский

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The Aitken Accelerated Gradient Algorithm for a Class of Dual‐Rate Volterra Nonlinear Systems Utilizing the Self‐Organizing Map Technique

International Journal of Robust and Nonlinear Control, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

ABSTRACT This article focuses on the parameter estimation issues for dual‐rate Volterra fractional‐order autoregressive moving average models. In case of sampling, we derive a identification model system and implement intersample output with help an auxiliary method. Then, combined self‐organizing map technique, propose Aitken multi‐innovation gradient‐based iterative algorithm. The parameters are estimated using algorithm, whereas differential orders determined Moreover, computational cost proposed algorithm is analyzed floating point operation. Finally, convergence analysis simulation examples show effectiveness

Language: Английский

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Parameter Estimation of Bilinear State‐Space Systems With Nonlinear Input via Enhanced Nadam Algorithm by Line Search Method

International Journal of Robust and Nonlinear Control, Journal Year: 2025, Volume and Issue: unknown

Published: May 5, 2025

ABSTRACT This article investigates the problem of parameter estimation for bilinear state‐space systems with nonlinear input. An innovative approach that combines Nesterov‐accelerated adaptive moment algorithm a line search strategy is proposed to address such complex systems. The uses backtracking method dynamically select an appropriate step‐size, thereby enhancing efficiency. effectiveness demonstrated through simulation experiments.

Language: Английский

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Correntropy‐Based Robust Interval‐Varying Recursive Estimation Method for Nonlinear Systems With Spline Networks and Outliers

International Journal of Robust and Nonlinear Control, Journal Year: 2025, Volume and Issue: unknown

Published: May 9, 2025

ABSTRACT Nonlinear system identification plays a key role in real‐world modeling. The spline networks can model the nonlinearity with high precision without prior knowledge of nonlinear structure. This paper examines problem Hammerstein systems outliers by using to describe nonlinearity. To avoid redundant computation, two sub‐models are derived, one local parameters and other global linear parameters. By exploiting insensitivity correntropy outliers, correntropy‐based robust interval‐varying recursive estimation method is presented. proposed not only models unknown computational efficiency but also under premise that total distribution observed data unknown. superiority algorithm validated simulation experiments.

Language: Английский

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Multi‐Stage Auxiliary Model Based Recursive Least Squares Estimation for Pseudo‐Linear System With ARMA Noise

International Journal of Adaptive Control and Signal Processing, Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

ABSTRACT This paper focuses on the parameter estimation problem for pseudo‐linear systems with autoregressive moving average noise. In order to reduce computational complexity of identification algorithms, original system is decomposed into three submodels and a three‐stage auxiliary model‐based recursive generalized extended least squares (3S‐AM‐RGELS) algorithm proposed based hierarchical principle. The convergence analysis provided show that error can converge zero under presented 3S‐AM‐RGELS algorithm. Finally, numerical simulations demonstrate effectiveness algorithms.

Language: Английский

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Separable synchronous auxiliary model adaptive momentum estimation strategy for a time-varying system with colored noise from on-line measurements

ISA Transactions, Journal Year: 2024, Volume and Issue: 157, P. 213 - 223

Published: Dec. 10, 2024

Language: Английский

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