Modeling the solar array design of remote sensing satellites based on adaptive neuro-fuzzy inference system

Modeling and analyzing systems, especially in complex systems with high dynamics, noise and uncertainty in understanding the behavior of systems and decision making is very important problem from long time ago. This paper shows that neuro-fuzzy systems can be used effectively to design the solar arrays of electrical power subsystem of a remote sensing satellite in conceptual design phase. In the design of neuro-fuzzy system, Takagi-Sugeno inference system, hybrid training algorithm and Gaussian membership functions are used. The simulation results obtained in this modeling have an accurate accuracy compared to the experimental data and classical calculations of remote sensing satellites