Passivity-Based Fuzzy ISMC for Wind Energy Conversion Systems With PMSG

Subramaniam, Ramasamy; Joo, Young Hoon

doi:10.1109/tsmc.2019.2930743

Cited by 50 publications

(25 citation statements)

References 41 publications

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“…A wind turbine, with fixed-pitch, can be described by the following group of mathematical equations [18,19]:…”

Section: Wind Turbine Modelingmentioning

confidence: 99%

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Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

Khan¹,

Khan²,

Khan³

et al. 2021

Turk J Elec Eng & Comp Sci

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The electrical power extracted from a wind energy conversion system (WECS) tends to be inconsistent due to the intermittent nature of the wind. This issue is addressed by formulating a maximum power point tracking (MPPT) control strategy that optimizes the power extraction from the WECS under a wide range of wind speed profiles. This research article focuses on the formulation of a nonlinear neuro-adaptive backstepping integral sliding mode control (NABISMC) based MPPT strategy for a standalone, variable speed, fixed-pitch WECS equipped with a permanent magnet synchronous generator (PMSG). The proposed paradigm is a hybrid of the conventional backstepping and the integral sliding mode control (ISMC) based MPPT schemes. The effectiveness of the control strategy devised is guaranteed through numerical simulations carried out in Matlab/Simulink for a 3 kW PMSG-WECS under a stochastic wind speed profile. Further validation is guaranteed by giving a detailed performance comparison analysis of the proposed MPPT control strategy with the conventional feedback linearization control (FBLC), proportional integral derivative (PID) control, sliding mode control (SMC), and standard neuro-adaptive integral sliding mode control (NAISMC) based MPPT strategies, where the proposed strategy is found superior to all the stated strategies in terms of offering more accurate MPPT, lower steady-state error, faster dynamic response and lesser chattering.

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“…A wind turbine, with fixed-pitch, can be described by the following group of mathematical equations [18,19]:…”

Section: Wind Turbine Modelingmentioning

confidence: 99%

“…Now, considering z 2 in (19) as a virtual controller that acts as a stabilization function and it can be expressed as follows: (19) yields:…”

mentioning

confidence: 99%

Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

Khan¹,

Khan²,

Khan³

et al. 2021

Turk J Elec Eng & Comp Sci

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“…Thus far, several research efforts have been made which explore the application of passivitybased controllers for PMSG driven systems. In [17], a PBC-based fuzzy sliding-mode controller is proposed. However, the controller design of the proposed combined strategy is complex due to the mathematical model.…”

Section: Introductionmentioning

confidence: 99%

Energy-Based Combined Nonlinear Observer and Voltage Controller for a PMSG Using Fuzzy Supervisor High Order Sliding Mode in a Marine Current Power System

et al. 2021

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A permanent magnet synchronous generator (PMSG) in s grid-connected tidal energy conversion system presents numerous advantages such as high-power density and ease of maintenance. However, the nonlinear properties of the generator and parametric uncertainties make the controller design more than a simple challenge. Within this paper we present a new combined passivity-based voltage control (PBVC) with a nonlinear observer. The PBVC is used to design the desired dynamics of the system, while the nonlinear observer serves to reconstruct the measured signals. A high order sliding-mode based fuzzy supervisory approach is selected to design the desired dynamics. This paper addresses the following two main parts: controlling the PMSG to guarantee the maximum tidal power extraction and integrate into to the grid-side converter (GSC), for this the new controller is proposed. The second task is to regulate the generated reactive power and the DC-link voltage to their references under any disturbances related to the machine-side converter (MSC). Furthermore, the robustness of the controller against parameter changes was taken into consideration. The developed controller is tested under parameter variations and compared to benchmark nonlinear control methods. Numerical simulations are performed in MATLAB/Simulink which clearly demonstrates the robustness of the proposed technique over the compared control methods. Moreover, the proposed controller is also validated using a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.

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“…In [22], a robust adaptive passivity-based control scheme for a class of openloop unstable nonlinear systems with actuator saturation in proposed. The authors in [23], investigated a passivity-based control combined with a fuzzy control and SMC by constructing a suitable fuzzy function. However, the controller design of the proposed combined strategy is complicated due to the mathematical.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Energy-Based Modified Super Twisting Algorithm and Factional Order PID Control for Performance Improvement of PMSG Dedicated to Tidal Power System

et al. 2021

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The majority of marine current conversion technologies are based on permanent magnet synchronous generators (PMSG) due to its numerous advantages such as high-power density, low cost, and favorable electricity production. However, nonlinear properties of the generator and parameter uncertainties, makes the controller design more than a simple challenge. This paper proposes a new adaptive passivity-based (PB) modified super twisting algorithm (PBSTA) for control performance improvement (low tracing errors, fast convergence response, robustness) of a PMSG based marine current energy conversion system under swell effect and parameter uncertainties. The proposed approach combines a new PB current control (PBCC) with a new adaptive modified super twisting algorithm through a fuzzy logic supervisor. A new adaptive fractional order PID (FO-PID) controller is introduced to design the desired dynamics of the system. The main contributions and motivation of this work include the extraction of maximum power from the tidal current, integrating it to the grid and making the closed loop system passive. This is possible by reshaping system energy and introducing a damping term that compensates the nonlinear terms by a damped way and not by cancellation. Two steps are needed to design the proposed controller: the first step includes the derivation of reference current based on the reference torque using adaptive FO-PID. In the second step, the overall control law is computed by the proposed PBSTA. The exponential stability and error convergence of the proposed controller are analytically proven. The developed controller is tested under parameter variations and it is compared to benchmark nonlinear control methods such as sliding mode. Extensive investigation under MATLAB/Simulink, demonstrates clearly that the proposed technique provides higher efficiency and robustness over the benchmark nonlinear control methods.

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Passivity-Based Fuzzy ISMC for Wind Energy Conversion Systems With PMSG

Cited by 50 publications

References 41 publications

Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

Energy-Based Combined Nonlinear Observer and Voltage Controller for a PMSG Using Fuzzy Supervisor High Order Sliding Mode in a Marine Current Power System

Intelligent Energy-Based Modified Super Twisting Algorithm and Factional Order PID Control for Performance Improvement of PMSG Dedicated to Tidal Power System

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