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In this study, an adaptive, supervisory, and hybrid fuzzy controllers as well as a fuzzy estimator are developed based on experimental and simulation data and expert's knowledge of the normal working of diagnostic systems. The advantage of the developed control system is that it has fewer parameters to tune; it also makes the system adaptable for changing environments or malfunctions; and provides the supervision of the overall performance of the engine management system. For the fuzzy estimator part of the system we employ the least square and gradient methods for the premise and consequent of the rule. This study introduces a new design method for FDI module. It also provides an efficient and easy to implement control system that can be incorporated into existing module with minimum changes, adjustment, and cost.