Controller design for reduced order model of SEPIC converter

Padhi, Binod Kumar; Padhy, Satya Narayan; Bhuyan, Kanhu Charan

doi:10.1109/scopes.2016.7955696

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…Note that it is necessary to estimate an additional state: the output voltage v o given by (23). The integral action, given by (20), can also be included in the control law.…”

Section: Sepic Ccm Sepic Dcmmentioning

confidence: 99%

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Adaptive and Nonlinear Control Techniques Applied to SEPIC Converter in DC-DC, PFC, CCM and DCM Modes Using HIL Simulation

et al. 2018

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Abstract:In this paper, we propose adaptive nonlinear controllers for the Single-Ended Primary Inductance Converter (SEPIC). We also consider four distinct situations: AC-DC, DC-DC, Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). A comparative analysis between classic linear and nonlinear approaches to regulate the control loop is made. Three adaptive nonlinear control laws are designed: Feedback Linearization Control (FLC), Passivity-Based Control (PBC) and Interconnection and Damping Assignment Passivity-Based Control (IDAPBC). In order to compare the performance of these control techniques, numerical simulations were made in Software and Hardware in the Loop (HIL) for nominal conditions and operation disturbances. We recommend adaptive controllers for the two different situations: Adaptive Passivity-Based Feedback Linearization Control (APBFLC) for the PFC (Power Factor Correction) AC-DC system and IDAPBC-BB (IDAPBC Based on Boost converter) for the regulator DC-DC system.

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“…Note that it is necessary to estimate an additional state: the output voltage v o given by (23). The integral action, given by (20), can also be included in the control law.…”

Section: Sepic Ccm Sepic Dcmmentioning

confidence: 99%

“…[15,22] use observers and immersion techniques. In [23], the fourth order transfer function of SEPIC is reduced to second order using the Pade approximation method, where the designed compensator closely follows the original system's response. Furthermore, Ref.…”

Section: Revised Sepic As a Boost Converter And Derived Equationsmentioning

confidence: 99%

Adaptive and Nonlinear Control Techniques Applied to SEPIC Converter in DC-DC, PFC, CCM and DCM Modes Using HIL Simulation

et al. 2018

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“…To reduce the model computation time, maintain tractability with higher-order converters and subsequently simplify the controller design step when using these inherently laborious modelling techniques, researchers have looked at developing reduced order models [34][35][36][37]. These models present a trade-off between accuracy and controller design complexity.…”

mentioning

confidence: 99%

A Unified Rule-Based Small-Signal Modelling Technique for Two-Switch, Non-Isolated DC–DC Converters in CCM

Masike

Gitau

Adam³

2022

Energies

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The inherent non-linear behavior of switch-mode power supplies complicates the task of computing their linear models, which are essential for a model-oriented control design of DC–DC converters. In a model-oriented control design approach, the accuracy of the plant model directly influences the performance of the control system as the plant parameters tend to be linked to the controllers’ gains. Moreover, the extractions of linear dynamic models of high-order non-linear plants such as DC–DC converters are laborious and mathematically intractable. Therefore, in this paper, a generalized expression that represents either the audio-susceptibility or the control-to-output voltage transfer function for voltage-mode control is proposed. The proposed generalization reduces the task of computing the small-signal model of a given converter to simple calculations of coefficients of generalized transfer function/expression. It is shown that the coefficients of the generalized model can be deduced by inspection, directly from the circuit diagram, allowing the whole model to be computed by inspection. Additionally, the proposed modelling technique will be shown to have secondary use of verifying accuracy even when conventional modelling techniques such as state-space averaging or circuit averaging are used.

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