Multi-objective Optimization of FIVR Control Loop

Fully Integrated Voltage Regulators (FIVR) are integral part of the power delivery network of high-performance server microprocessor chips. FIVR is a switched-inductor, multiphase on-chip buck voltage regulator. FIVR is also a closed loop control system that regulates the output voltage. The FIVR control loop consists of a Type-III op-amp compensator (CPS) that has programmable passive RC components. The CPS RC values need to be chosen from a wide range to optimize the performance of the FIVR control loop. In this paper Evolutionary Multi-objective Optimization (EMO) Algorithms are proposed for the optimization of FIVR control loop. The multi-objective functions and the constraints for optimizing the FIVR control loop are developed. Examples demonstrate that the EMO methods perform better than the existing Single-objective Optimization (SO) methods.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/edaps64431.2024.10988456
Primary Topic
Industrial Technology and Control Systems
Type
article
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Multi-objective Optimization of FIVR Control Loop

Srikrishnan Venkataraman, Srinivasan Govindan, Amit Kumar, Beomseok Choi
Industrial Technology and Control Systems
article

Multi-objective Optimization of FIVR Control Loop

Srikrishnan Venkataraman, Srinivasan Govindan, Amit Kumar, Beomseok Choi
article en

Abstract

Fully Integrated Voltage Regulators (FIVR) are integral part of the power delivery network of high-performance server microprocessor chips. FIVR is a switched-inductor, multiphase on-chip buck voltage regulator. FIVR is also a closed loop control system that regulates the output voltage. The FIVR control loop consists of a Type-III op-amp compensator (CPS) that has programmable passive RC components. The CPS RC values need to be chosen from a wide range to optimize the performance of the FIVR control loop. In this paper Evolutionary Multi-objective Optimization (EMO) Algorithms are proposed for the optimization of FIVR control loop. The multi-objective functions and the constraints for optimizing the FIVR control loop are developed. Examples demonstrate that the EMO methods perform better than the existing Single-objective Optimization (SO) methods.

Intel (United States) (US), Intel (India) (IN)
Openalex Percentile: Top 63%
Industrial Technology and Control Systems
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