Cuttlefish Optimization Algorithm in Autotuning of Altitude Controller of Unmanned Aerial Vehicle (UAV)

摘要

Due to the variety of applications of multirotor and fixed-wing unmanned aerial vehicles (UAVs) and their highly energy-limited flight time, there is a strong need for optimization methods in order to ensure the best tracking quality of reference signals changes. In this paper, the use of one of the most recent population-based, bio-inspired, automatic search algorithm for optimal parameters of fixed-gain controller according to the predefined cost function, was proposed. This is cuttlefish algorithm (CFA) which is a new, batch, meta-heuristic algorithm, which mimics the mechanism of colour changing behaviour used by the cuttlefish to solve numerical global optimization problems, and in the paper - to explore the three-dimensional, limited space of parameters of the most commonly used controller type, i.e. PID. This controller was proposed in order to control the altitude of unmanned aerial vehicle. A comparative studies were conducted for the closed-loop control system with the model of unmanned quadrotor helicopter and following controllers: PID (tuned by the CFA), classical PD, fuzzy PD and fractional-order PD controller (tuned by the Particle Swarm Optimization algorithm). In optimization procedure by the use of cuttlefish algorithm, a minimization of an exemplary cost function, i.e. Integral of Absolute Error (IAE), was introduced.