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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
MEHDI AKBARI
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Artificial Tune of Fuel Ratio: Design a Novel SISO Fuzzy Backstepping Adaptive Variable Structure Control FARZIN Piltan; MOHAMMAD Mansoorzadeh; SAEED ZARE; FATEMEH Shahryarzadeh; MEHDI AKBARI
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (292.134 KB)

Abstract

This paper examines single input single output (SISO) chattering free variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. VSC methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. The main goal is to guarantee acceptable fuel ratio result and adjust. The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. The input represents the function between variable structure function, error and the rate of error. The outputs represent fuel ratio, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBSAVSC) is validated through comparison with VSC and proposed method. Simulation results signify good performance of trajectory in presence of uncertainty torque load. DOI:http://dx.doi.org/10.11591/ijece.v3i2.2092
Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine Farzin Piltan; Mansour Bazregar; Marzieh Kamgari; Mojdeh Piran; Mehdi Akbari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 3, No 1: March 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (445.46 KB) | DOI: 10.11591/ijai.v3.i1.pp36-48

Abstract

In this research, manage the Internal Combustion (IC) engine modeling and a multi-input-multi-output artificial intelligence baseline chattering free sliding mode methodology scheme is developed with guaranteed stability to simultaneously control fuel ratios to desired levels under various air flow disturbances by regulating the mass flow rates of engine PFI and DI injection systems. Nevertheless, developing a small model, for specific controller design purposes, can be done and then validated on a larger, more complicated model. Analytical dynamic nonlinear modeling of internal combustion engine is carried out using elegant Euler-Lagrange method compromising accuracy and complexity. The fuzzy inference baseline sliding methodology performance was compared with a well-tuned baseline multi-loop PID controller through MATLAB simulations and showed improvements, where MATLAB simulations were conducted to validate the feasibility of utilizing the developed controller and state estimator for automotive engines. The proposed tracking method is designed to optimally track the desired FR by minimizing the error between the trapped in-cylinder mass and the product of the desired FR and fuel mass over a given time interval.
Co-Authors Farzin Piltan FARZIN Piltan FATEMEH Shahryarzadeh Mansour Bazregar Marzieh Kamgari MOHAMMAD Mansoorzadeh Mojdeh Piran SAEED ZARE