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In recent decades, one of the scientists' main concerns has been to improvethe accuracy of satellite attitude, regardless of the expense. The obviousresult is that a large number of control strategies have been used to addressthis problem. In this study, an adaptive neuro-fuzzy integrated (ANFIS)satellite attitude estimation and control system was developed. The controlleris trained with the data provided by an optimal controller. A pulse modulatoris used to generate the right ON/OFF commands of the thruster actuator. Toevaluate the performance of the AN-FIS controller in closed-loop simulation, anANFIS observer is used to estimate the attitude and angular velocities of thesatellite using magnetometer, sun sensor and data gyro data. In addition, a newANFIS system will be proposed and evaluated that can jointly control andestimate the system. The performance of the ANFIS controller is compared to theoptimal PID controller in a Monte Carlo simulation with different initialconditions, disturbance and noise. The results show that the ANFIS controllercan surpass the optimal PID controller in several aspects, including time andsmoothness. In addition, the ANFIS estimator is examined and the resultsdemonstrate the high ability of this designated observers. Both the control andestimation phases are simulated by a single ANFIS subsystem, taking intoaccount the high capacity of ANFIS, and the results of using the ANFIS modelare demonstrated.

An adaptive neuro-fuzzy model for attitude estimation and 2 control a 3 DOF system