Modeling and Simulation of Variable Limits on Conditional Anti-Windup PI Controllers for VSC-Based Devices

Murad, Mohammed Ahsan Adib; Liu, Muyang; Milano, Federico

doi:10.1109/tcsi.2021.3073103

Cited by 10 publications

(3 citation statements)

References 21 publications

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“…[33] Moreover, the back-calculation coefficient determines how aggressively the accumulated integral error is to be adjusted when the saturation occurs. [34,35] Finally, the controller designs, incorporating the anti-windup mechanism for output saturation, were correctly tuned using an untrained dataset in alignment with the provided sensitivity analysis. Figure 4C visualizes the schematic control diagram along with associated PID gains in Table 2.…”

Section: Sensitivity and Feedback Controlmentioning

confidence: 99%

Machine learning‐enabled optimization of melt electro‐writing three‐dimensional printing

Abdullah,

Ozarslan,

Farshi

et al. 2024

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Melt electrowriting (MEW) is a solvent‐free (i.e., no volatile chemicals), a high‐resolution three‐dimensional (3D) printing method that enables the fabrication of semi‐flexible structures with rigid polymers. Despite its advantages, the MEW process is sensitive to changes in printing parameters (e.g., voltage, printing pressure, and temperature), which can cause fluid column breakage, jet lag, and/or fiber pulsing, ultimately deteriorating the resolution and printing quality. In spite of the commonly used error‐and‐trial method to determine the most suitable parameters, here, we present a machine learning (ML)‐enabled image analysis‐based method for determining the optimum MEW printing parameters through an easy‐to‐use graphical user interface (GUI). We trained five different ML algorithms using 168 MEW 3D print samples, among which the Gaussian process regression ML model yielded 93% accuracy of the variability in the dependent variable, 0.12329 on root mean square error for the validation set and 0.015201 mean square error in predicting line thickness. Integration of ML with a control feedback loop and MEW can reduce the error‐and‐trial steps prior to the 3D printing process, decreasing the printing time (i.e., increasing the overall throughput of MEW) and material waste (i.e., improving the cost‐effectiveness of MEW). Moreover, embedding a trained ML model with the feedback control system in a GUI facilitates a more straightforward use of ML‐based optimization techniques in the industrial section (i.e., for users with no ML skills).

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Section: Sensitivity and Feedback Controlmentioning

confidence: 99%

Machine learning‐enabled optimization of melt electro‐writing three‐dimensional printing

Abdullah,

Ozarslan,

Farshi

et al. 2024

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“…A particular advantage of the definition of the event functions h is that they can represent any non‐linear equation. This is particularly relevant when modelling control limiters with variable limits, such as the current limiters of the Voltage Sourced Converters (VSCs) utilised in power ‐electronics‐based devices [120].…”

Section: Modellingmentioning

confidence: 99%

Power system modelling as stochastic functional hybrid differential‐algebraic equations

Milano

Liu

Murad³

et al. 2022

IET Smart Grid

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This paper presents the software tools developed for the research project Advanced Modelling for Power System Analysis and Simulation (AMPSAS) funded by Science Foundation Ireland from 2016 to 2021. The main objective of AMPSAS was the development of novel analytical and computational tools to understand, efficiently design, and optimise ever-changing modern power systems and smart grids, through modelbased approaches. In particular, the paper discusses (i) stochastic differential equations for modelling power systems, which are subject to large stochastic perturbations (e.g. wind and solar generation); (ii) the effect of controller and modelling imperfections, for example, delays, discontinuities, and digital signals, on both local and area-wide regulators in power systems; and (iii) the stability analysis and dynamic performance of power systems modelled through stochastic, delay and hybrid implicit differential-algebraic equations. The software tool developed during the execution of AMPSAS integrates areas of applied mathematics, automatic control, and computer science. Several implementation features and open challenges of this software tool are also discussed in the paper. A variety of examples that illustrates the features of this software tool are based on a dynamic model of the all-island Irish transmission system.

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“…In the event of faults or voltage dips, the power and voltage control will act to change the current orders and cause the outer PI controls windup [15]. Anti-windup schemes have to be implemented, which require additional sensors and calculation [15], [16]. The alternative design proposed in this paper can simplify grid-following control implementation.…”

Section: Introductionmentioning

confidence: 99%

An Alternative Control Structure for Grid-Following Converters of Inverter-Based Resources

Miao

Zhou

Fan

et al. 2023

IEEE Open J. Power Energy

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In this paper, an alternative control structure of grid-following control is proposed and applied in inverter-based resources (IBRs). An IBR's grid-following control normally employs Power/Voltage (P/V) control strategy to control the output real power and the voltage at the point of common coupling bus. Compared with the conventional cascade structure, the proposed alternative control structure follows the principle of robust cascade structure. It has the same inner current control for current order tracking while the outer loop is redesigned. This new design leads to power order and voltage order tracking without use of integral control. This point alone is advantageous since an integral control has the known issue of saturation and anti-freezing has to be implemented. The purpose of such structure is to be robust against the uncertainty in the inner feedback system. We implement the robust cascade control and examine its capability of accommodating choke filter parameter variation. Besides this capability, the control's weak grid stability performance and low voltage ride through performance are also examined. Using nonlinear analytical model-based eigenvalue analysis and nonlinear dynamic simulation, we find that the robust cascade control structure can be designed to accommodate choke filter parameter variation, improve weak grid stability, and avoid overvoltage after fault clearance.

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Modeling and Simulation of Variable Limits on Conditional Anti-Windup PI Controllers for VSC-Based Devices

Cited by 10 publications

References 21 publications

Machine learning‐enabled optimization of melt electro‐writing three‐dimensional printing

Machine learning‐enabled optimization of melt electro‐writing three‐dimensional printing

Power system modelling as stochastic functional hybrid differential‐algebraic equations

An Alternative Control Structure for Grid-Following Converters of Inverter-Based Resources

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