NEW HEURISTIC ALGORITHMS FOR ROLLING AIR FRAME AERODYNAMIC PARAMETERS ESTIMATION

Abstract

In this research, based on heuristic optimization algorithms, three new strategies are developed for Aerodynamic Parameters Estimation (APE) of one pair ON-OFF actuator rolling airframe. In the 1st method namely EAM-PSO the aerodynamic parameters are directly estimated. While, the next two algorithms called EBM-PSO and SEBM-PSO are two-step strategies. In the 1st step the aerodynamic forces and moments are estimated, then after passing through a designed smoothing filter, in the 2nd step aerodynamic parameters are estimated. In EBM-PSO all the aerodynamic parameters are estimated at once by solving one optimization problem. In SEBM-PSO the APE is converted to solve four separate optimization problems. A modified particle swarm optimization algorithm is developed and used in estimation process. The performance of proposed algorithms is compared with that of state of the art algorithm EKF. The simulation results show that SEBM-PSO and EBM-PSO are better than EAM-PSO in term of accuracy and run time.