2010 · 19 citations · 5 references
EngineeringFuzzy ModelingFlying RobotFlight ControlNonlinear Helicopter ModelFuzzy Control SystemNonlinear System IdentificationGenetic AlgorithmSystems EngineeringIntelligent MethodsNonlinear ControlFuzzy LogicMechatronicsIntelligent ControlSystem IdentificationAerospace EngineeringMechanical SystemsVibration ControlAir Vehicle System
This paper presents an implementation of soft computing methodologies, like genetic algorithm and fuzzy logic, in identification and control of 2DOF nonlinear helicopter model (Humusoft CE 150). The genetic algorithm is proposed for identification of the physical structure of helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to elevation and azimuth fuzzy logic Mamdani type controllers design in a simulation mode. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments.
5
Output regulation of nonlinear systems
Alberto Isidori, C.I. Byrnes · IEEE Transactions on Automatic Control · 1990 · 1.6K citations
Output tracking for a non-minimum phase dynamic CTOL aircraft model
Claire J. Tomlin, John Lygeros, Luca Benvenuti et al. · 2002 · 88 citations
Engineering, Aerospace Engineering, Aerospace Simulation +12