Design Online Artificial Gain Updating Sliding Mode Algorithm: Applied to Internal Combustion Engine

Abstract

This paper presents an online Artificial Fuzzy sliding Gain Scheduling Sliding Mode Control (AFSGSMC) design and its application to internal combustion (IC) engine high performance nonlinear controller in the presence of uncertainties and external disturbance. The fuzzy online tune sliding function in fuzzy sliding mode controller is based on Mamdanis fuzzy inference system (FIS) and it has multi input and multi output. The input represents the function between sliding function, error and the rate of error. The output represents the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The performance of the AFSGSMC was compared with the IC engine controller based on sliding mode control theory (SMC). Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance