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Abstract:In the paper a Sugeno architecture based hardware implemented neuro adaptive inference system's training algorithm is presented. The block diagram of the neuro-adaptive inference system output computing implemented in hardware is discussed, and the implementation in reconfigurable circuit of real-time parameter tuning is presented. The proposed system functionality based on measurements achieved is demonstrated. The resulted architecture has a very high processing speed, and the parameter adaptation works in parallel with the output processing. The proposed architecture can also be used for different training algorithms' development.

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This paper presents a framework based on embedded SOC systems, which allows the testing and use of control algorithms implemented on FPGA circuits. For monitoring and parameterization a real-time Linux operating system was used. In this paper different methods for data exchange between the operating system and the control unit were introduced. The delay between the operating system and the control unit during the data exchange was studied and the measurement results discussed reflect the real-time functionality of the system.