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.

Dynamic aerodynamic parameter estimation using a dynamic particle swarm optimization algorithm for rolling airframes

“…Based on the above six-degree-offreedom (6DOF) equations of motion, a simulation model is used to generate needed test data. During interval time 0 to 6 s, an actuation signal δ(t) = sin(2pt) + Asin(pt + φ) is applied to the vehicle [14]. Simulation outputs are saved with a sampling time of 0.002 s and used as the measurement data.…”

“…Similar to that of EBM-PSO in [14], the proposed DAPE is also a two-step estimation strategy. In the first step, the aerodynamic forces and moments are estimated; then, after passing through a designed smoothing filter, in the second step aerodynamic parameters are estimated.…”

“…The authors of current article, in Ref. [14], developed three new strategies for APE, based on a modified version of PSO: The first algorithm, namely EAM-PSO, estimates the aerodynamic parameters directly. The next two algorithms called EBM-PSO and SEBM-PSO are two-step strategies.…”

“…The dynamic optimization algorithm is an adapted version of dynamic hybrid particle swarm optimization (DHPSO) algorithm, developed in [15]. Similar to that of EBM-PSO in [14], the DAPE algorithm is also a two-step strategy. In the first step, the aerodynamic forces and moments are estimated; then, after passing through a designed smoothing filter, in the second step, aerodynamic parameters are estimated, while the numerical integration process of dynamic equations is eliminated, and hence, the computational run time is decreased.…”