2015
DOI: 10.1007/s11768-015-4062-1
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Nonlinear optimized adaptive trajectory control of helicopter

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Cited by 23 publications
(14 citation statements)
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“…Dynamic inversion (DI) controller is selected to be implemented in order to control the quadrotor position and attitude. This controller has been successfully implemented in many aircraft [25,40,41]. DI is a nonlinear control strategy based feedback linearization that can be applied in several control-loops in a system.…”
Section: Control System Designmentioning
confidence: 99%
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“…Dynamic inversion (DI) controller is selected to be implemented in order to control the quadrotor position and attitude. This controller has been successfully implemented in many aircraft [25,40,41]. DI is a nonlinear control strategy based feedback linearization that can be applied in several control-loops in a system.…”
Section: Control System Designmentioning
confidence: 99%
“…The intelligent control system based on neural networks and fuzzy logic is introduced to the linear and nonlinear systems to enhance the control performance or to control the systems which were difficult to obtain their dynamic model [25]. Meguenni et al designed a fuzzy integral sliding mode controller to control a quadrotor [26].…”
mentioning
confidence: 99%
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“…A small electric antenna can be defined as an antenna which possesses geometrical dimension that is small in comparison to the wavelength of the electromagnetic fields they radiate [1,2]. These antennas have various applications in unmanned vehicles [3,4,5], radars [6], and wireless communication [7,8] which motivate researchers to develop these antennas based on their needs. Metamaterial structures which are first developed by V. G. Veselago in 1967 provide electromagnetic properties that do not exist in nature and include negative index of refraction, negative permittivity, or negative permeability [9].…”
Section: Introductionmentioning
confidence: 99%
“…Also the PD controller cannot control the unpredicted nonlinear properties of dynamic model, which may degrade the control performance critically. To find a more robust controller to tolerate these uncertainties, various method such as fuzzycompensator, fuzzy self-gain-tuner, fuzzy-PD controller and adaptive neural networks were introduced [1][2][3][4][5][6]. In these papers, the proportional and derivative gains of the fuzzy-PD controller were modified by the two-input fuzzy controller.…”
Section: Introductionmentioning
confidence: 99%