The Experts below are selected from a list of 409095 Experts worldwide ranked by ideXlab platform
Liuping Wang - One of the best experts on this subject based on the ideXlab platform.
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Discrete Model predictive controller design using laguerre functions
Journal of Process Control, 2004Co-Authors: Liuping WangAbstract:In Model Predictive Controller (MPC) design, the traditional approach of expanding the future control signal uses the forward shift operator to obtain the linear-in-the-parameters relation for predicted output. As a consequence, in case of rapid sampling, complicated process dynamics and/or high demands on closed-loop performance, satisfactory approximation of the control signal requires a very large number of forward shift operators, and leads to poorly numerically conditioned solutions and heavy computational load when implemented on-line. In this paper, by using a performance specification on the exponential change rate of the control signal, a more appropriate expansion, related to Laguerre net-works, is introduced and analyzed. It is shown that the number of terms used in the optimization procedure can be reduced to a fraction of that required by the usual procedure. By relaxing the constraint on the exponential change rate of the control signal and allowing arbitrary complexity in describing the trajectory, the proposed approach becomes equivalent to the traditional approach in MPC design. Closed-loop stability of the proposed Model predictive control system is analyzed by using terminal state variable constraints.
Aissa Bouzid - One of the best experts on this subject based on the ideXlab platform.
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Discrete Model predictive control based maximum power point tracking for pv systems overview and evaluation
IEEE Transactions on Power Electronics, 2018Co-Authors: Abderezak Lashab, Dezso Sera, Josep M Guerrero, Laszlo Mathe, Aissa BouzidAbstract:The main objective of this work is to provide an overview and evaluation of Discrete Model-predictive control (MPC)-based maximum power point tracking (MPPT) for photovoltaic systems. A large number of MPC-based MPPT methods have been recently introduced in the literature with very promising performance; however, an in-depth investigation and comparison of these methods has not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC-based MPPT methods applied to various common power converter topologies. The performance of MPC-based MPPT is directly linked with the converter topology, and it is also affected by the accurate determination of the converter parameters; sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers is assessed according to the EN 50530 standard, using detailed simulation Models, and validated by experimental tests. The analysis in this work aims to present useful insight for practicing engineers and academic researchers when selecting the maximum power point tracker for their application.
Irrine Budi Sulistiawati - One of the best experts on this subject based on the ideXlab platform.
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Implementing Discrete Model of Photovoltaic System on the Embedded Platform for Real-Time Simulation
Energies, 2020Co-Authors: Aryuanto Soetedjo, Irrine Budi SulistiawatiAbstract:This paper presents the development of a Discrete Model of a photovoltaic (PV) system consisting of a PV panel, Maximum Power Point Tracking (MPPT), a dual-axis solar tracker, and a buck converter. The Discrete Model is implemented on a 32-bit embedded system. The goal of the developed Discrete PV Model is to provide an efficient way for evaluating several algorithms and Models used by the PV system in real-time fashion. The proposed Discrete Model perfectly matches the continuous and Discrete Model simulated with MATLAB-SIMULINK. The real-time performance is tested by running the Model to simulate the PV system, where the fastest time sampling of 1 ms is achieved by the buck converter Model, while the longest time sampling of 100 ms is achieved by the solar tracker Model. Moreover, a novel method is proposed to optimize the net energy, which is calculated by subtracting the energy consumed by the tracker from the PV energy generated. The proposed net energy optimization method varies the operation time interval of the solar tracker under high and low solar irradiation conditions. Based on the real-time simulation of the Discrete Model, our approach increases the net energy by 29.05% compared to the system without the solar tracking and achieves an increase of 1.08% compared to the existing method.
Zhao Xiu-chun - One of the best experts on this subject based on the ideXlab platform.
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Research on Discrete Model Reference Adaptive Control System of Electric Vehicle
2006 SICE-ICASE International Joint Conference, 2006Co-Authors: Xu Guo-kai, Song Peng, Zhao Xiu-chunAbstract:The drive control system is one of the key technologies for electric vehicle. It can improve the electric vehicle performance using the Discrete-time Model reference adaptive control methods. In this paper, the Discrete Model reference adaptive control system of HS2000 electric vehicle is discussed. Firstly, the Discrete Model of EV is presented. Based on it the design of the adaptive control is made, and the rule of Discrete Model reference adaptive control is proven. The results of simulation show that adaptive control has favorable characteristic than the PID control system.
Abderezak Lashab - One of the best experts on this subject based on the ideXlab platform.
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Discrete Model predictive control based maximum power point tracking for pv systems overview and evaluation
IEEE Transactions on Power Electronics, 2018Co-Authors: Abderezak Lashab, Dezso Sera, Josep M Guerrero, Laszlo Mathe, Aissa BouzidAbstract:The main objective of this work is to provide an overview and evaluation of Discrete Model-predictive control (MPC)-based maximum power point tracking (MPPT) for photovoltaic systems. A large number of MPC-based MPPT methods have been recently introduced in the literature with very promising performance; however, an in-depth investigation and comparison of these methods has not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC-based MPPT methods applied to various common power converter topologies. The performance of MPC-based MPPT is directly linked with the converter topology, and it is also affected by the accurate determination of the converter parameters; sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers is assessed according to the EN 50530 standard, using detailed simulation Models, and validated by experimental tests. The analysis in this work aims to present useful insight for practicing engineers and academic researchers when selecting the maximum power point tracker for their application.
