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Substantial developments in optimizing control methods for different purposes have been made in the field of fuzzy control in recent years. However, most of them are based on a known system model, whereas in practice such models are not usually available due to the complexity of the plant to be controlled. In this paper, an adaptive fuzzy controller optimizes the altitude control of a helicopter, in a way that does not depend on a process model. The algorithm does not need a mathematical model of the plant or its approximation in the form of a Jacobian matrix. Neither is it necessary to know the desired response at each instant of time, nor is there a need for sample data of the plant qualitative knowledge, and auxiliary fuzzy controllers enable the main controller to accomplish its task in real time.