Adaptive fuzzy event-triggered fast fixed-time filtering backstepping formation control for underactuated USVs with LOS range and bearing angle constraints

Ocean Engineering, Год журнала: 2025, Номер 325, С. 120674 - 120674

Опубликована: Фев. 27, 2025

Язык: Английский

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Iterative parameter estimation for a class of fractional-order Hammerstein nonlinear systems disturbed by colored noise

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 28, 2025

Considering the existence of nonlinearity and fractional-order phenomena in practical environments, this paper investigates parameter estimation methods for a class Hammerstein nonlinear systems disturbed by colored noise. The are based on decomposition strategy, separating identification from system parameters. Meanwhile, is divided into two subsystems, which linear block using hierarchical principle. To overcome problem redundant estimation, over-parameterization method key item separation used, respectively. Then, two-stage gradient-based iterative algorithm term derived, auxiliary model used to compute unmeasurable variables. In addition, we analyze computational efficiencies proposed algorithms. simulation results indicate that algorithms effective. Finally, evaluated through battery model. show well agreement with real outputs.

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Март 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.

Язык: Английский

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

Nonlinear Dynamics, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Апрель 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.

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Апрель 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

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Май 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.

Язык: Английский

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Joint State and Parameter Estimation for the Fractional‐Order Wiener State Space System Based on the Kalman Filtering

International Journal of Adaptive Control and Signal Processing, Год журнала: 2025, Номер unknown

Опубликована: Май 7, 2025

ABSTRACT This paper mainly investigates the joint estimation of parameters and states for fractional‐order Wiener state space model. Based on Kalman filter principle, a generalized recursive least squares algorithm with forgetting factor is proposed. In addition, filtering‐based presented, which reduces influence colored noise parameter estimation. A gradient identification introduced to estimate order fractional‐order. Under persistent excitation conditions, analysis indicates that proposed can system. simulation example given confirm algorithms are effective.

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Май 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.

Язык: 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, Год журнала: 2025, Номер unknown

Опубликована: Апрель 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.

Язык: Английский

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