Application of Fuzzy Logic on Internal Combustion Engines

Controllers PID (proportional - integral - derivative) are particularly suitable for control of dynamic processes which can be modeled by systems of first and second order. Internal combustion engines (ICE) are modeled as high order systems that have non-linearities. The presence of noise, jitter and other external factors can cause variations in parameters and sudden changes in the structure of the model that hamper the PID controller tuning. In this context, the PID controller tuning becomes important and a Fuzzy inference system is adopted in addition to a PID controller to improve the response to transients. The Fuzzy logic was used to implement controllers for idle speed of an ICE, getting a robust response to disturbance and interference in the control loop. This article assesses the performance of PID and Fuzzy controllers from a simulation model in Matlab - Simulink on an ICE operand in idle speed. The error values and variation of error resulting from PID controller action are determined as input data for linguistic Fuzzy rules that constitute the Fuzzy logic controller (FLC). This action provides the reduction of overshoot and reduces time of ICE's accommodation control allowing a stable idling operation.