Abstract 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.
Cuttlefish Optimization Algorithm in Autotuning of Altitude Controller of Unmanned Aerial Vehicle (UAV)
12.11.2017
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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