Identification of Wiener models for dynamic and steady‐state performance with application to solid oxide fuel cell
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Publication:5213844
DOI10.1002/asjc.2038zbMath1432.93067OpenAlexW2911411721WikidataQ128469407 ScholiaQ128469407MaRDI QIDQ5213844
Publication date: 6 February 2020
Published in: Asian Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/asjc.2038
System identification (93B30) Application models in control theory (93C95) Mathematical modeling or simulation for problems pertaining to systems and control theory (93-10)
Related Items (2)
Optimization of control strategy for a low fuel consumption vehicle engine ⋮ Correlation analysis algorithm-based multiple-input single-output Wiener model with output noise
Cites Work
- Unnamed Item
- Unnamed Item
- Fault diagnosis and fault-tolerant control strategies for non-linear systems. Analytical and soft computing approaches
- Advanced control of industrial processes. Structures and algorithms.
- Identification of systems containing linear dynamic and static nonlinear elements
- Combined parametric-nonparametric identification of block-oriented systems
- Computationally efficient model predictive control algorithms. A neural network approach
- Nonlinear Adaptive Control of a Hybrid Fuel Cell Power System for Electric Vehicles - a Lyapunov Stability Based Approach
- Latent-variable Nonlinear Model Predictive Control Strategy for a pH Neutralization Process
- Tuning Method for Fractional Complex Order Controller Using Standardized k -Chart: Application to Pemfc Control
- Hybrid Model Predictive Power Management of A Fuel Cell-Battery Vehicle
- Nonparametric identification of Wiener systems by orthogonal series
- Performance Improvement of Fuel Cells Using Perturbation‐Based Extremum Seeking and Model Reference Adaptive Control
- Nonlinear MPC Controller Design for AIR Supply of PEM Fuel Cell Based Power Systems
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