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Optimization-based robust fractional-order controllers design for multiple-input single-output systems with time delays

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MEASUREMENT & CONTROL 2024年

作者： Ben Moussa, Noura Chetoui, Manel Amairi, Messaoud Univ Gabes Natl Engn Sch Gabes Res Lab Modeling Anal & Control Syst Rue Omar Ibn Khattab Gabes 6029 Tunisia

This paper deals with the design of fractional order PID controllers based on nonlinear optimization for multi-input single-output (MISO) systems with time delays. Two approaches are used to obtain optimal controllers' parameters. The first uses time-domain specifications and consists of minimizing time-domain criteria without constraints. The second uses frequency-domain specifications and imposes the open-loop phase to be flat in a specified frequency band. Simulations results and a comparative study are presented to verify the effectiveness of each approach.

关键词： Fractional PID nonlinear optimization multi-input single-output system time-delay

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Physics-Based Lumped-Parameter Modeling of Automotive Canister Fuel Purge

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JOURNAL OF DYNAMIC systemS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 2016年第7期138卷 071008-071008页

作者： Franchek, Matthew Ebrahimi, Behrouz Grigoriadis, Karolos Makki, Imad Univ Houston Dept Mech Engn Houston TX 77204 USA Ford Motor Co R&D Dept Detroit MI 48125 USA

A physics-based model is presented to estimate the flow rate out of the fuel canister purged into the intake manifold. The lumped parameters of the model, including canister capacitance and flow resistance, are employed to obtain a first-order multi-input and single-output dynamic model. The vacuum pressure in the intake manifold and the fuel tank pressure serve as inputs, and the purged fuel flow rate is considered as the model output. The model does not require cumbersome computation, thereby allowing direct implementation in the fueling control to compensate for the extra fuel in regulation of the stoichiometric air-fuel ratio.

关键词： canister purge model physics-based modeling multi-input single-output system parameter estimation

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Physics-Based Lumped-Parameter Modeling of Automotive Canister Fuel Purge

Physics-Based Lumped-Parameter Modeling of Automotive Canist...

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American Control Conference

作者： Francheck, Matthew Ebrahimi, Behrouz Grigoriadis, Karolos Makki, Imad

ISBN: (纸本)9781479986842

A physics-based canister fuel purge flowrate model based on fluid mechanics and thermodynamics principles is presented in this paper to improve the tailpipe emission control in automotive applications. The aim of the paper is to derive a lumped-parameter model for the canister that estimates the flowrate out of the canister purged into the intake manifold. The lumped parameters of the model, including canister capacitance and flow resistance are employed to obtain a first-order multi-input and single-output (MISO) dynamic model. The vacuum pressure in the intake manifold and the fuel tank pressure serve as inputs and the mass flowrate is considered as the model output. Gradient descent system identification method is used to estimate the model parameters based on experimental data collected at Ford Motor Company. The advantage of the model is that it does not require cumbersome integral or differential computational methods and is easy to implement for fueling control purposes. Hence, it allows direct implementation in the fueling control to compensate for the extra fuel benefiting the stoichiometric air/fuel regulation in the engine catalyst.

关键词： Canister Purge Model Physics-Based Modeling multi-input single-output system Parameter Estimation

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multi-input single-output nonlinear adaptive digital filters using recurrent neural networks

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2001年第8期E84A卷 1942-1950页

作者： Lu, JM Lin, H Wang, XQ Yahagi, T Chiba Univ Grad Sch Sci & Technol Chiba 2638522 Japan

Linear adapt ivf, digital filters are applied to various fields for their simplicity ill the design and implementation. Considering many kinds of nonlinearities inherent in practical systems, however, nonlinear adaptive filtering will be more desirable. This paper presents a design method for multi-input single-output nonlinear adaptive digital filters using recurrent neural networks. Furthermore. in comparison with this method and the method based oil the conventional linear theory, if the proposed method is used. better results can be obtained, and, it is possible that the learning efficiency is improved, because the parallel learning is carried out in this method. Finally the results of computer simulation are presented to illustrate the effectiveness of the proposed method.

关键词： multi-input single-output system recurrent neural network nonlinear adaptive digital filter

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