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 adapti...
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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-inputsingle-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.
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 ...
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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.
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 employ...
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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.
This paper deals with the design of fractional order PID controllers based on nonlinear optimization for multi-inputsingle-output (MISO) systems with time delays. Two approaches are used to obtain optimal controllers...
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This paper deals with the design of fractional order PID controllers based on nonlinear optimization for multi-inputsingle-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.
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