Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

Yang, Bo; Yu, Tao; Shu, Hongchun; Zhu, Dena; Sang, Yiyan; Jiang, Lin

doi:10.1063/1.5032266

Cited by 18 publications

(22 citation statements)

References 46 publications

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“…The conditions (21) must be satisfied simultaneously, and by using the change of variable (42) gives:…”

Section: Proof Of Theoremmentioning

confidence: 99%

“…Takagi-Sugeno models have been broadly utilized to represent nonlinear integer-order systems. However, the fuzzy Takagi-Sugeno scheme remains very efficient for nonlinear fractional order systems (FOS) [42][43][44]. Therefore, the use of fractional-order Takagi-Sugeno (FOTS) models to represent nonlinear FOS will be introduced in this paper.…”

Section: Introductionmentioning

confidence: 99%

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Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables

et al. 2019

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This paper presents a new procedure for designing a fractional order unknown input observer (FOUIO) for nonlinear systems represented by a fractional-order Takagi–Sugeno (FOTS) model with unmeasurable premise variables (UPV). Most of the current research on fractional order systems considers models using measurable premise variables (MPV) and therefore cannot be utilized when premise variables are not measurable. The concept of the proposed is to model the FOTS with UPV into an uncertain FOTS model by presenting the estimated state in the model. First, the fractional-order extension of Lyapunov theory is used to investigate the convergence conditions of the FOUIO, and the linear matrix inequalities (LMIs) provide the stability condition. Secondly, performances of the proposed FOUIO are improved by the reduction of bounded external disturbances. Finally, an example is provided to clarify the proposed method. The obtained results show that a good convergence of the outputs and the state estimation errors were observed using the new proposed FOUIO.

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“…The conditions (21) must be satisfied simultaneously, and by using the change of variable (42) gives:…”

Section: Proof Of Theoremmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables

et al. 2019

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“…Different from integer‐order rational transfer functions, the fractional‐order operator possesses the infinite memory and takes into consideration the whole history of input signals, which effectively reduces the chattering phenomenon of conventional SMC . Passive FOSMC is designed for photovoltaic systems to achieve maximum power point tracking under various operating conditions, and FOSMC greatly improves the robustness of the closed‐loop system against various disturbances . For microgrid with distributed generator, authors propose a passivity‐based FOSMC of a supercapacitor energy storage system to achieve more flexible control performance as compared with conventional control methods .…”

Section: Introductionmentioning

confidence: 99%

“…23 Passive FOSMC is designed for photovoltaic systems to achieve maximum power point tracking under various operating conditions, and FOSMC greatly improves the robustness of the closed-loop system against various disturbances. 24 For microgrid with distributed generator, authors propose a passivity-based FOSMC of a supercapacitor energy storage system to achieve more flexible control performance as compared with conventional control methods. 25 To overcome the overconservativeness of conventional SMC methods, a perturbation observer-based FOSMC is developed for photovoltaic inverter, which significantly enhances the transient performance.…”

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confidence: 99%

Fractional‐order sliding mode control for damping of subsynchronous control interaction in DFIG‐based wind farms

Xiong

Wang

et al. 2019

Wind Energy

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This paper proposes a fractional-order sliding mode control (FOSMC) based on feedback linearization (FL) technique to mitigate subsynchronous control interaction (SSCI) in doubly fed induction generator (DFIG)-based wind farms connected to series-compensated transmission lines. A linearized form of the studied system is obtained with the use of FL, which leads to reduced system order and small computational burden. Then the FOSMC is designed for grid-side converter (GSC) to stabilize SSCI and to provide a considerable robustness against external disturbances and parameter uncertainties. For FOSMC parameter tuning, genetic algorithm (GA) is performed through MATLAB/SIMULINK. Time-domain simulation are carried out to evaluate the effectiveness of the FOSMC in mitigating SSCI at varied operating conditions, and the superior performance of the proposed control is demonstrated as compared with conventional vector control (VC), feedback linearization sliding mode control (FLSMC), high-order sliding mode control (HOSMC). KEYWORDS doubly fed induction generator, fractional-order sliding mode control, subsynchronous control interaction 1 | INTRODUCTION Subsynchronous resonance (SSR) of wind farms is a condition where wind turbines exchange energy with the grid at one or more natural frequency below the fundamental frequency. 1 A new type of SSR, known as subsynchronous control interaction (SSCI), has been detected worldwide in recent years. 2 Without the involvement of mechanical components, rapidly developing SSCI can lead to serious equipment damage and loss of power generation if proper countermeasures are not taken instantly. Furthermore, many studies have demonstrated that doubly fed induction generator (DFIG) wind farms are susceptible to SSCI due to the active participation of fast-acting converter control. 3,4 Therefore, it is urgent to develop effective SSCI mitigation techniques to ensure the safe operation of grid-connected DFIG-based wind farms.The design of SSCI damping controls has received much attention from industry and academia. A number of control methods using FACTS devices are proposed to mitigate SSCI, such as gate-controlled series capacitor (GCSC), 5 thyristor-controlled series capacitor (TCSC), 6 and static synchronous compensator (STATCOM). 7 As compared with FACTS-based damping controls, modification of wind turbine converter (WTC) control is an economical and convenient solution to SSCI. Since grid-side converter (GSC) has the damping capability similar to STATCOM with an extra advantage of lower cost, various damping methods are proposed based on the improvement of existing GSC control. A washout block is embedded into GSC stator voltage control for SSCI mitigation. 8 A supplemental damping signal is added to the summing junction of GSC's outer control. 9 GSC's d-axis inner control loop is also utilized to alleviate SSCI with speed deviation as input control signal (ICS). 10 GSC provides the greater flexibility of adding SSCI damping controls, but its damping capability is limited to 30% of...

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“…It is quite hard to determine these gain parameters unless the designers have expert knowledge about grid-connected PV systems. Nonlinear sliding mode controllers are designed in [23,24] to control the VSI for grid-connected PV systems. However, the sliding mode controller is sensitive to unmodeled dynamics of the system.…”

Section: Introductionmentioning

confidence: 99%

Partial Feedback Linearizing Model Predictive Controllers for Multiple Photovoltaic Units Connected to Grids through a Point of Common Coupling

Orchi

Mahmud

2018

Electronics

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In this paper, partial feedback linearizing model predictive controllers are designed for grid-connected systems comprising multiple photovoltaic (PV) units where these units are connected through a point of common coupling (PCC). The proposed controllers are designed for voltage source inverters (VSIs) based on comprehensive dynamical models of grid-connected PV systems with the proposed topology. The proposed partial feedback linearization scheme decouples multiple PV units in the forms of several reduced-order subsystems and enables linear controller design through the linear continuous-time receding horizon model predictive control scheme. The proposed partial feedback linearization scheme also considers dynamic interactions among multiple PV units as external noises or disturbances and decouples these noises. This paper includes the noise decoupling capability of the partial feedback linearization for grid-connected PV systems with multiple PV units which are connected through a PCC. Simulation results clearly demonstrate the effectiveness of the proposed scheme under different operating conditions as compared to an existing proportional integral controller.

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Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

Cited by 18 publications

References 46 publications

Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables

Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables

Fractional‐order sliding mode control for damping of subsynchronous control interaction in DFIG‐based wind farms

Partial Feedback Linearizing Model Predictive Controllers for Multiple Photovoltaic Units Connected to Grids through a Point of Common Coupling

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