Summary: | Modeling and control of engine systems are vital due to wide range of their applications. As it is
obvious stability is the minimum requirement in any control system, however the proof of stability
is not trivial especially in the case of nonlinear systems. One of the most active research areas in
field of internal combustion engine (IC engine) is control of the fuel ratio. The strategies for control
of engines are classified into two main groups: classical and non-classical methods, where the
classical methods used the conventional control theory and non-classical methods used the
artificial intelligence theory such as fuzzy logic, neural networks and/or neurofuzzy. One of the
best nonlinear robust controllers which can be used in uncertainty nonlinear systems is sliding
mode controller (SMC). Chattering phenomenon is the main challenge in this controller. Fuzzy
logic and neuro control have been applied successfully in many applications. Therefore stable
control of an internal combustion engine is challenging because it has uncertain dynamic
parameters. This research presents design a fuzzy sliding mode control with improved in sliding
mode algorithm which offers a model-free sliding mode methodology. The fuzzy sliding mode
controller is designed as a 49 rules Mamdani’s error-based fuzzy sliding-like equivalent part
instead of nonlinear dynamic equation of equivalent part. Various performance indices like the
minimum error, trajectory, disturbance rejection, and chattering control are used for comparison.
|