- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Nonlinear Acoustic Dynamics in Nanoelectromechanical Waveguides
摘要： A novel adaptive radial basis function neural network H-in?nity control strategy with robust feedback compensator using linear matrix inequality (LMI) approach is proposed for micro electro mechanical systems vibratory gyroscopes involving parametric uncertainties and external disturbances. The proposed system is comprised of a neural network controller, which is designed to mimic an equivalent control law aimed at relaxing the requirement of exact mathematical model and a robust feedback controller, which is derived to eliminate the effect of modeling error and external disturbances. Based on the Lyapunov stability theorem, it is shown that H-in?nity tracking performance of the gyroscope system can be achieved, all variables of the closed-loop system are bounded, and the effect due to external disturbances on the tracking error can be attenuated effectively. Numerical simulations are investigated to demonstrate that the satisfactory tracking performance and strong robustness against external disturbances can be obtained using the proposed adaptive neural H-in?nity control strategy with robust feedback compensator by LMI technique.
关键词： neural network control,Adaptive control,H-In?nity Control
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - High Efficiency Semi-Transparent Organic Photovoltaics
摘要： A novel adaptive radial basis function neural network H-in?nity control strategy with robust feedback compensator using linear matrix inequality (LMI) approach is proposed for micro electro mechanical systems vibratory gyroscopes involving parametric uncertainties and external disturbances. The proposed system is comprised of a neural network controller, which is designed to mimic an equivalent control law aimed at relaxing the requirement of exact mathematical model and a robust feedback controller, which is derived to eliminate the effect of modeling error and external disturbances. Based on the Lyapunov stability theorem, it is shown that H-in?nity tracking performance of the gyroscope system can be achieved, all variables of the closed-loop system are bounded, and the effect due to external disturbances on the tracking error can be attenuated effectively. Numerical simulations are investigated to demonstrate that the satisfactory tracking performance and strong robustness against external disturbances can be obtained using the proposed adaptive neural H-in?nity control strategy with robust feedback compensator by LMI technique.
关键词： H-In?nity Control,Adaptive control,neural network control
更新于2025-09-19 17:13:59
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[IEEE 2019 8th International Conference on Systems and Control (ICSC) - Marrakesh, Morocco (2019.10.23-2019.10.25)] 2019 8th International Conference on Systems and Control (ICSC) - Performance Evaluation of Neural Network Controlled Grid-Connected Photovoltaic System for Power Quality Enhancement
摘要： This paper studies a neural network (NN) control for three-phase grid-connected Photovoltaic (PV) system. This study aims to improve the performances of the system, ensure a high quality of the Total Harmonic Distorsion and extract the maximum power while ensuring unity power factor. A neural network controller is used instead of the two PI regulation loop for grid currents. The Levenberg Marquardt (LM) algorithm is used to train the NN controller and the validation and training data of the utilized neural controller are obtained by simulation of the entire system with the PI controllers calculated for variation of solar irradiance. The simulation study shows that the neural controller indicates significantly more enhanced performance than that of the PI controller, including faster response times, lower overshoot and Total Harmonic Distortion (THD).
关键词： Neural Network Control,Levenberg Marquardt Algorithm,Photovoltaic System,Total Harmonic Distortion,Power Quality
更新于2025-09-16 10:30:52
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[IEEE 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD) - Istanbul, Turkey (2019.3.21-2019.3.24)] 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD) - MPPT Control Strategies for Photovoltaic Applications: Algorithms and Comparative Analysis
摘要： In this paper, five Maximum Power Point Tracking algorithms for PV system are presented, simulated and discussed. Solar Photovoltaic energy has become a popular device of the renewable energies. The power-voltage (P-V) characteristic of PV cells is naturally nonlinear dependent of insolation and temperature degrees. Accordingly, the maximum power point change with the atmospheric conditions. In order to ameliorate the overall efficiency, a control technique for the duty cycle of the DC/DC power converter is required. The aim of this paper is to present a thorough assessment of various MPPT techniques. Five different methods are discussed which are: the Perturbation-Observation (P&O) method, the Incremental Conductance (INC) method, the Fuzzy Logic Control (FLC), the Neural Network control (NNC) and the Sliding mode control (SMC). These algorithms are modeled and simulated with a specific PV chain consisting of a 50W PV panel and a Boost converter in order to evaluate their performances.
关键词： Neural Network Control (NNC),Simulation,Maximum Power Point Tracking (MPPT),Incremental Conductance (INC),DC/DC converter,Fuzzy Logic Control (FLC),Sliding Mode Control (SMC),Perturbation-Observation (P&O),Modeling
更新于2025-09-11 14:15:04