Results 61 to 70 of about 1,110 (179)

Continuous-time Hammerstein model identification utilizing hybridization of Augmented Sine Cosine Algorithm and Game-Theoretic approach

Results in Engineering
The widespread use of dynamic systems has greatly simplified various human-operated tasks. However, the complex and nonlinear nature of these systems has posed challenges in determining their structure due to heavy reliance on modeling for theoretical ...
Mohd Helmi Suid, Mohd Ashraf Ahmad, Ahmad Nor Kasruddin Nasir, Mohd Riduwan Ghazali, Julakha Jahan Jui   +4 more
doaj   +1 more source

Improved Intelligent Identification of Hammerstein-Wiener Systems by Particle Swarm Optimization and K-Means Clustering

Chemical Engineering Transactions, 2019
This paper considers the robust identification of Hammerstein-Wiener systems in the presence of Gaussian or non-Gaussian noises. An improved intelligent identification scheme is exploited by combining particle swarm optimization (PSO) and K-means ...
Zhu Wang, Haoran An, Xiong-Lin Luo
doaj   +1 more source

Identification of uncertain MIMO Wiener and Hammerstein models

Computers & Chemical Engineering, 2011
Abstract Several approaches can be found in the literature to perform the identification of block oriented models (BOMs). In this sense, an important improvement is to achieve robust identification to cope with the presence of uncertainty. In this work, two special and widely used BOMs are considered: Hammerstein and Wiener models. The models herein
Biagiola, Silvina Ines, Figueroa, Jose Luis   +1 more
openaire   +2 more sources

Study on dynamic hysteresis characteristic modeling and parameter identification methods for high-voltage piezoelectric actuators

Xibei Gongye Daxue Xuebao
High-voltage piezoelectric actuators are widely used in the field of active vibration control of aerospace structures due to their advantages of strong load capacity, large nominal thrust, and fast response.
LI Weiguang, LIU Ke, WANG Hui, DENG Qingtian, YANG Zhichun   +4 more
doaj   +1 more source

Data-driven modeling approaches for pressure drop prediction in a multi-phase flow system

Communications in Science and Technology
Accurate prediction of pressure drops in multi-phase flow systems is essential for optimizing processes in industries such as oil and gas, where operational efficiency and safety depend on reliable modeling.
Nezar M. Alyazidi, Aiman F. Bawazir, Ala S. AL-Dogai   +2 more
doaj   +1 more source

Application of Improved WOA in Hammerstein Parameter Resolution Problems under Advanced Mathematical Theory

Journal of Applied Mathematics
With the development of industrial demand, precise identification of system models is currently required in the field of industrial control, which limits the whale search algorithm.
Lu Zhao, Jiangjun Liu, Yuan Li
doaj   +1 more source

Low-Complexity Frequency-Dependent Linearizers Based on Parallel Bias-Modulus and Bias-ReLU Operations

IEEE Access
This paper introduces low-complexity frequency-dependent (memory) linearizers designed to suppress nonlinear distortion in analog-to-digital interfaces.
Deijany Rodriguez Linares, Hakan Johansson   +1 more
doaj   +1 more source

Double-layered nonlinear model predictive control based on Hammerstein–Wiener model with disturbance rejection

Measurement + Control, 2018
This paper presents the double-layered nonlinear model predictive control method for a continuously stirred tank reactor and a pH neutralization process that are subject to input disturbances and output disturbances at the same time.
Hongbin Cai, Ping Li, Chengli Su, Jiangtao Cao   +3 more
doaj   +1 more source

Decoupled Parameter Identification for Network-Based Nonlinear Systems Using Correlation Analysis and Optimal Gradient Theory

Mathematics
For the identification problem of Hammerstein models, this paper proposes a decoupled identification algorithm that combines the correlation analysis with the optimal gradient-based iterative algorithm.
Qi Dong, Haolong Jiang, Qinglei Bu, Qinyao Liu   +3 more
doaj   +1 more source