Comparative analysis of classical and fuzzy PI algorithms for the three-phase synchronous generator

Corcau, Jenica Ileana; Dincă, Liviu

doi:10.1109/lindi.2011.6031135

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…The data for simulations have been obtained from literature [2]. There are two important methods for aircraft parameter identification: identification in the time domain or in the frequency domain [2,6,7,36,37]. Here, for UAV parameter identification, the Minnesota research team used the first method because it is physically more intuitive and straightforward as the UAV dynamics is mostly represented by using time domain state-space models [2].…”

Section: Simulation Resultsmentioning

confidence: 99%

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Adaptive backstepping flight control for a mini‐UAV

Lungu

2012

Adaptive Control & Signal

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The paper presents the design of a mini-unmanned aerial vehicle (UAV) attitude controller using the backstepping method. Starting from the nonlinear dynamic equations of the mini-UAV, by using the backstepping method, the authors of this paper obtained the expressions of the elevator, rudder, and aileron deflections, which stabilize the UAV at each moment to the desired values of the attitude angles. The attitude controller controls the attitude angles, the angular rates, the angular accelerations, and other variables describing the UAV longitudinal and lateral motions. The designed controller has been implemented in Matlab/Simulink environment, and its effectiveness has been tested with a campaign of numerical simulations using data from the UAV flight tests.

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Section: Simulation Resultsmentioning

confidence: 99%

“…Many research projects have been performed for an integrated framework in recent years [4][5][6][7][8][9]. The central paradigm is a model-based development environment for the UAV where different design tools and techniques can be formulated, deployed, and applied [2].…”

Section: Antecedents and Motivationsmentioning

confidence: 99%

Adaptive backstepping flight control for a mini‐UAV

Lungu

2012

Adaptive Control & Signal

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“…In a nanopositioning system, the transfer function of the plant is identified using the frequency response analysis in analogy with (3). The transfer function is represented by a second order model, as in the equation below:…”

Section: A Linear Dynamics Modelmentioning

confidence: 99%

“…One of the most important goals of the fuzzy logic controller is improving the dynamic characteristics of the system as compared with conventional controllers [2]. A comparative analysis of the fuzzy logic controller and its counterpart, the conventional controller, has proven that the fuzzy logic controller shows better dynamics behaviour [3]. Further, the fuzzy logic controller can be used in conjunction with conventional control techniques to augment them and simplify their design [4].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-Enhanced Dual-Loop Control Strategy for Precise Nanopositioning

Altaher¹,

Aphale²

2017

2017 International Symposium on Computer Science and Intelligent Controls (ISCSIC)

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Vibration problems are inherent to most precision positioning systems. These systems are lightly damped and highly susceptible to mechanical resonance at any sudden change in the voltage applied to the nanopositioning platform. These systems also exhibit nonlinearity, such as hysteresis and creep. The traditional approach uses a combination of damping controllers and tracking controllers to deal with nonlinearity and resonance respectively. The classical approach is based on sole use of the integral controller (l) or proportional integral (PI) as a tracking controller to treat nonlinearity; this paper employs a hybrid feedback scheme, using the fuzzy logic controller as a correction tracking controller in in conjunction with the conventional tracking controllers. The damping controllers utilised in this work to damp the mechanical resonance of the nanopositioning platform are the Integral Resonant Controller (IRC), the Positive Velocity and Position Feedback (PVPF), and the Positive Position Feedback Controller (PPF). The proposed fuzzy logic controller delivers improved dynamic tracking performance characteristics with less vibration in comparison with the conventional tracking method because the fuzzy logic controller can handle nonlinearity and vibration via its rules and membership functions. The use of fuzzy Gaussian membership function can alleviate the appearance of mechanical resonance.

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Comparative analysis of classical and fuzzy PI algorithms for the three-phase synchronous generator

Cited by 2 publications

References 5 publications

Adaptive backstepping flight control for a mini‐UAV

Adaptive backstepping flight control for a mini‐UAV

Fuzzy-Enhanced Dual-Loop Control Strategy for Precise Nanopositioning

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