Evolutionary Design on-line Sliding Fuzzy Gain Scheduling Sliding Mode Algorithm: Applied to Internal Combustion Engine

Abstract

Refer to this research, a position on-line fuzzy sliding gain scheduling sliding mode control (AFSGSMC) design and application to internal combustion engine has proposed in order to design high performance nonlinear controller in the presence of uncertainties and external disturbance. Even though, sliding mode controller (SMC) is used in wide range areas but it has the following disadvantages: chattering and equivalent dynamic formulation. The fuzzy on-line tuneable sliding function in fuzzy sliding mode controller is based on Mamdani’s fuzzy inference system (FIS) and it has one input and one output. The input represents the function between sliding function, error and the rate of error. The outputs represent the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The fuzzy sliding mode methodology is on-line tune the sliding function based on self tuning coefficient methodology. The performance of the AFSGSMC is validated through comparison with previously developed 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.