Identification of Nonlinear Air-Bearing System Using Particle Swarm Optimization Technique

Suitable identification of a nonlinear system can improve the controller design and its analysis. In this paper, the parameters of the nonlinear air-bearing system of the satellite simulator have been obtained using the Particle Swarm Optimization (PSO) method. This estimation is done in two stages. In the first step, a situational maneuver is carried out using reaction wheels, and the torque and angular velocity values around three axes are stored. In the second step, using the data bank, the PSO method is implemented and the parameters of the nonlinear system are estimated. Here, the parameters of the moment of inertia and the difference between the center of mass and the center of rotation are estimated. To assess the effectiveness of the proposed method, The PSO approach is compared with the least square error method. The comparison results indicate that the presented method has a 3.5% higher accuracy.