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Air Pollution Reduction Based on Intelligent Nonlinear Control Methodology
보안공학연구지원센터(IJHIT) International Journal of Hybrid Information Technology Vol.8 No.1 2015.01 pp.173-180
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
This paper expands a Multi Input Multi Output (MIMO) fuzzy baseline control (FBC) which controller coefficient is off-line tuned by gradient descent algorithm. The main goal is to adjust the optimal value for fuel ratio (FR) in motor engine. The fuzzy inference system in proposed methodology is works based on Mamdani-Lyapunov fuzzy inference system (FIS). To reduce dependence on the gain updating factor coefficients of the fuzzy methodology, PID baseline method is introduced. This new method provides an optimal setting for other factors which created by PID baseline method. The gradient descent methodology is off-line tune all coefficients of baseline fuzzy based on mathematical optimization methodology. Simulation results signify good performance of fuel ratio in presence of different torque load and external disturbance.
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