Precise Attitude Control of CubeSats: PID Controller with Particle Swarm Optimization

CubeSats are widely used in numerous scientific, educational, and commercial applications. CubeSat models exhibit nonlinear dynamics, strong coupling, and sensitivity to external Disturbances. In light of these challenges, there is a crucial need for a robust and optimal attitude controller to deal with these complexities in all conditions and achieve the desired control angles throughout CubeSats' missions. One of the most efficient and sufficient control systems that could handle the desired requirements with low cost, simplicity, and ease of implementation is the Proportional-Integral-Derivative Controller (PID). Besides, the performance enhancement of the PID controllers relies on its gain selection. Therefore, the optimality of PID gains will increase its capability to overcome the dynamic system's uncertainty and external Disturbances. From this point of view, this work will present a Particle Swarm Optimization (PSO) technique that has several benefits, including a very effective global search algorithm to optimize the controller's gain. CubeSat's dynamic model is implemented in Matlab (Simulink), a PID controller designed with longitudinal and lateral-directional channels. Then, a modified cost function will be applied to the optimal algorithm to estimate the desired gains. Finally, the simulation results show the controller superiority rather in system performance or the control effort exerted.