2002 · 17 citations · 3 references
EngineeringAerospace EngineeringMechatronics EngineeringArtificial IntelligenceFlight DynamicsFlight MechanicsAircraft ControlAttitude ControlControl Of Dynamical SystemsControl SystemsControl TheorySystem IdentificationAttitude Control SystemsFuzzy Control SystemsIntelligent ControlNeural Network ControlNonlinear Aircraft DynamicsNonlinear Attitude ControlNonlinear System IdentificationNonlinearity
This paper is studying on the 3-DOF attitude control of a helicopter. The characteristic to be heavily coupled with inputs and outputs, and the serious nonlinearity appear in the flying helicopter system. Due to these characteristics of a helicopter, people apply the nonlinear control, multi-variable control or optimal control for the attitude control of helicopter. It is too hard to define the relations of input and output in a view of dynamics, therefore others also study this theme in a view of AI control-(artificial intelligent control) based on the fuzzy theory or neural network. But in the hovering, those characteristics-heavily coupled system and nonlinearity, reduce considerably. In this paper, we assume that those characteristics are able to be disregarded in hovering. The model helicopter system that is constructed with three independent SISO (single input single output) systems, is acquired by system identification method, and then the PD-control (proportional derivative control) is applied individually to three independent SISO systems for a 3-DOF attitude control of a model helicopter in hovering. Those assumptions are verified by the experiment.
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System identification—Theory for the user
Naresh K. Sinha · Automatica · 1989 · 9.2K citations
Digital control of dynamic systems
H.N. Koivo · Automatica · 1983 · 2K citations
Engineering, Electrical Engineering, Systems Engineering +13
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T. John Koo, Frank Hoffmann, Bruno Sinopoli et al. · IFAC Proceedings Volumes · 1998 · 37 citations