GENETIC ALGORITHM BASED FOPID CONTROLLER FOR NANO-SATELLITE ATTITUDE CONTROL

Abstract

Nano-satellites are very popular among researchers today because they are more affordable and easier to use than most large satellites. The system performance on nano-satellites needs to be improved for better by using fractional order PID (FOPID) controllers which have never been tested on unstable systems on nano-satellite objects. The PID controller development produces two fractional power parameters called the FOPID controller, which makes it even more attractive. The genetic algorithm (GA) produces the optimal computation value on the FOPID controller because it has been proven to have better performance and is improved by the ITAE performance index. Based on the analysis of responses in a steady-state in the form of overshoot, rise time and settling time on the three-axis stabilized nano-satellite attitude control, namely roll, pitch, and yaw is concluded that the FOPID controller is superior to the classic PID controller that has been previously studied. The effect of the two parameters of the FOPID controller on an unstable system for nano-satellite attitude control shows good performance results based on the ITAE performance index using the genetic algorithm (GA) method.