Journal of Science and Arts Year 2016, No. 4(37), pp. 407-416, 2016 ISSN: 1844 – 9581 Physics Section ORIGINAL PAPER FUZZY PID CONTROLLER FOR NANO-SATELLITE ATTITUDE CONTROL MOHAMMED CHESSAB MAHDI 1 _____________________________ Manuscript received: 12.08.2016; Accepted paper: 21.12.2016; Published online: 30.12.2016. Abstract. In this paper, a fuzzy PID controller has been suggested to use in attitude determination and control subsystem of kufasat equipped with three magnetic coils. Using the linearized equations of motion for a rigid body in space, the linearized stability, effectiveness and robustness of a fuzzy PID controller design were compared with that of a fuzzy PD controller design. The detailed design procedure of the fuzzy controllers is presented. When fuzzy PID controller is applied simulation results show that more precise attitude control is accomplished and less time of satellite maneuver is required comparing with applying fuzzy PD controller. Keywords: Fuzzy PID Controller; Attitude Control System; Nanosatellite; KufaSat. 1. INTRODUCTION The attitude determination and control subsystem (ADCS) is responsible of keeping the orientation of spacecraft in the space in addition to achieve the required maneuver. Keeping the orientation of spacecraft in the space called attitude stabilization. The attitude maneuver is the re-orientation process of changing one attitude to another. The ADCS collects the data from attitude sensors and process it to determine the current attitude of spacecraft. The ADCS then compares the current attitude with the desired attitude and use the difference between them by help of specified algorithm to activate appropriate actuators to remove or reduce the error. There are some control techniques available to use in the controller. Proportional-Integral-Derivative (PID) controller is the most widely used controller with feedback mechanism. It is one of the simplest control algorithms, so it is often the best choice in many applications [1]. The linear quadratic regulator (LQR) from optimal control theory is another control technique which expresses the control problem as a mathematical optimization, and it then looks for the best controller and used state-space approach to analyze such a system. Other control technique is based on fuzzy logic and does not need a mathematical model of the system, instead it use Linguistic rules to represent the knowledge, these rules come from an actual human expert who know how best to control the process [2]. This technique is suitable to the systems with complex or uncertain mathematics model. 1 Al-Furat Al-Awsat Technical University & University of Kufa, Iraq. E-mail: mchessab@yahoo.com .