A Design Fuzzy Logic Controller for a Permanent Magnet Wind Generator to Enhance the Dynamic Stability of Wind Farms

Rosyadi, Marwan; Muyeen, S. M.; Takahashi, Rion; Tamura, Junji

doi:10.3390/app2040780

Cited by 34 publications

(23 citation statements)

References 10 publications

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“…The first 200 data samples come from condition 1, the second 200 data samples from condition 2, and the third 200 data samples from condition 3. The centers for the agents are calculated in different conditions, so here the number of the centers for the fuzzy T-S multi-model is 19. The RMSE of the ABFT-SMM in this time is 0.0056, it is very close to the accuracy of the single condition, and the computation complexity is proper.…”

Section: Simulation Testsmentioning

confidence: 98%

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Agent Based Fuzzy T-S Multi-Model System and Its Applications

Zhao

2015

Applied Sciences

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Based on the basic concepts of agent and fuzzy T-S model, an agent based fuzzy T-S multi-model (ABFT-SMM) system is proposed in this paper. Different from the traditional method, the parameters and the membership value of the agent can be adjusted along with the process. In this system, each agent can be described as a dynamic equation, which can be seen as the local part of the multi-model, and it can execute the task alone or collaborate with other agents to accomplish a fixed goal. It is proved in this paper that the agent based fuzzy T-S multi-model system can approximate any linear or nonlinear system at arbitrary accuracy. The applications to the benchmark problem of chaotic time series prediction, water heater system and waste heat utilizing process illustrate the viability and the efficiency of the mentioned approach. At the same time, the method can be easily used to a number of engineering fields, including identification, nonlinear control, fault diagnostics and performance analysis.

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Section: Simulation Testsmentioning

confidence: 98%

“…Each rule of the fuzzy model can be seen as a local model, it means that the process of fuzzy modeling is the process of describing the action of the whole system by combining the local models [18,19].…”

Section: Fuzzy T-s Modelmentioning

confidence: 99%

Agent Based Fuzzy T-S Multi-Model System and Its Applications

Zhao

2015

Applied Sciences

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“…An alternative solution is to include a PID gain scheduling algorithm inside the controller, such as the cooperation between the PID controller and fuzzy logic algorithm [30], or logic-based supervisor strategy [31].…”

Section: Control Goalmentioning

confidence: 99%

Adaptive Control of Active Magnetic Bearing against Milling Dynamics

Lee

Chen

2016

Applied Sciences

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For improving the defects in milling processes caused by traditional spindle bearings, e.g., the dimensional discrepancy of a finished workpiece due to bearing wear or oil pollution by lubricant, a novel embedded cylindrical-array magnetic actuator (ECAMA) is designed for milling applications. Since ECAMA is a non-contact type actuator, a control strategy named fuzzy model-reference adaptive control (FMRAC) is synthesized to account for the nonlinearities of milling dynamics and magnetic force. In order to ensure the superior performance of spindle position regulation, the employed models in FMRAC are all constructed by experiments. Based on the experimental results, the magnetic force by ECAMA is much stronger than that by the traditional active magnetic bearing (AMB) design under the same test conditions and identical overall size. The efficacy of ECAMA to suppress the spindle position deviation with the aid of FMRAC has been verified as well via numerical simulations and practical metal cutting.

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“…If the V w is greater than V rw , then the output power of the PMSG is controlled by the pitch angle (β) control system. When V w ranges between cut-in V w (5 m/s) to rated V w (12 m/s), the β is set to 0°, since wind windmill energy is maximum at 0° [14], when V w is between V rw and the cut-out V w (24 m/s), the pitch angle is controlled to deliver windmill output (P g = 1), when the V w is above the cut-out V w the β is set to 90° because the energy of a windmill is the smallest at 90°. The control diagram is shown in Fig.…”

Section: Wind Energy Conversion Systemmentioning

confidence: 99%

“…[12][13][14]. The PMSG has a simple structure and high efficiency; it is expected to be installed in the next generation of WTG systems.…”

Section: Wind Energy Conversion Systemmentioning

confidence: 99%

Fuzzy Logic Controlled Dual Active Bridge Series Resonant Converter for DC Smart Grid Application

Nassor¹,

Yona²,

Senjyu³

2015

JEPE

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Abstract:Over the last few years, smart grids have become a topic of intensive research, development and deployment across the world. This is due to the fact that, through the smart grid, stable and reliable power systems can be achieved. This paper presents a fuzzy logic control for dual active bridge series resonant converters for DC smart grid application. The DC smart grid consists of wind turbine and photovoltaic generators, controllable and DC loads, and power converters. The proposed control method has been applied to the controllable load's and the grid side's dual active bridge series resonant converters for attaining control of the power system. It has been used for management of controllable load's state of charge, DC feeder's voltage stability during the loads and power variations from wind energy and photovoltaic generation and power flow management between the grid side and the DC smart grid. The effectiveness of the proposed DC smart grid operation has been verified by simulation results obtained by using MATLAB ® and PLECS ® cards.

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A Design Fuzzy Logic Controller for a Permanent Magnet Wind Generator to Enhance the Dynamic Stability of Wind Farms

Cited by 34 publications

References 10 publications

Agent Based Fuzzy T-S Multi-Model System and Its Applications

Agent Based Fuzzy T-S Multi-Model System and Its Applications

Adaptive Control of Active Magnetic Bearing against Milling Dynamics

Fuzzy Logic Controlled Dual Active Bridge Series Resonant Converter for DC Smart Grid Application

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