An improved particle swarm optimization and its application in maneuvering control laws design of the unmanned aerial vehicle

Abstract

An improved particle swarm optimization algorithm with dynamic population mechanism is introduced in this paper aiming at the optimal design of the maneuvering flight scheme of the unmanned aerial vehicle system which confronts complex nonlinear flight characteristics. The control law of the typical S maneuver in vertical plane is parameterized through spline method and the constraints are disposed by the penalty function method in a weighted objective function. A practical design example of the unmanned aerial vehicle maneuvering scheme is given at last, and the simulation results show the availability of the method proposed in this paper and also a good application prospects in the flight scheme optimal design of the unmanned aerial vehicles.