Hardware efficient digital auto-Tuning average current-mode controller

Timur Vekslender, Eli Abramov, Or Kirshenboim, Mor Mordechai Peretz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a new hardware efficient auto tuning for digitally controlled average current-mode (ACM) controllers. The auto-Tuning procedure extracts the required coefficients of the ACM controller to achieve tight voltage regulation as well as closed-loop dynamic performance that may be defined by the end-user. System stability is facilitated for wide operation range under parameters uncertainties and other variations. It is found that information of the change in the state-variables suffice for a successful and accurate closed-loop operation without the need of a detailed extraction of the values of the passive components. The algorithm is applicable upon power up of the SMPS and has been integrated into the soft-start routine of the converter, assuring tight and stable regulation of the output voltage under all scenarios. The effectiveness of the new digital auto-Tuning ACM controller is demonstrated on an experimental 500kHz, 12V-To-1.2V digitally controlled synchronous buck converter.

Original languageAmerican English
Title of host publication2017 IEEE 18th Workshop on Control and Modeling for Power Electronics, COMPEL 2017
ISBN (Electronic)9781509053261
DOIs
StatePublished - 18 Aug 2017
Event18th IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2017 - Stanford, United States
Duration: 9 Jul 201712 Jul 2017

Publication series

Name2017 IEEE 18th Workshop on Control and Modeling for Power Electronics, COMPEL 2017

Conference

Conference18th IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2017
Country/TerritoryUnited States
CityStanford
Period9/07/1712/07/17

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Modelling and Simulation

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