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Electro-optical pointing and tracking systems (EOPTS) have a wide range of military and civilian applications. The passive line of sight (LOS) stabilization systems are multi-input multi-output (MIMO) systems that are highly nonlinear and possess a strong coupling effect between their states. it presents a challenging systems to control. In this paper the analysis of the passive (EOPTS) stabilization system with the development of its nonlinear models is derived. Two different types of control algorithms are presented. The first controller is a classical fuzzy control. The controller presents a good technique that proves to be stable with high transient and tracking performances. The controller is applied to the LOS stabilization system and the simulation results are introduced. Next, A Model Reference Learning fuzzy Controller less dependant on the designer knowledge of the LOS stabilization system is proposed. Such controller possesses a learning mechanism that is able to form its rule-base by watching the system behavior. The learning mechanism utilizes a reference model that describes the desired performance. The designed process of the controller and simulation results of implementing the controller to the system is introduced. Finally, comparative analysis between the two developed controllers is conducted. It discusses the advantages and disadvantages of each controller algorithm.

An Assessment between Classical Fuzzy and Fuzzy Model Reference Learning Controller Design of Electro-Optical pointing and tracking System