Robust Control of Power Electronics and Drives

  • Robust Control of Power Electronics and Drives

Overview

This project generated fundamental and applied research outcomes in the area of control of power electronics and drives. These systems are used in a wide range of applications, including mining, hybrid vehicles and renewables. We captured advantages of traditional control approaches whilst capitalising on the additional flexibility inherent in modern Model Predictive Control formulations. This allowed us to develop high-performance strategies which give enhanced reliability and efficiency.

Model Predictive Control (MPC) is one of the key strategies in contemporary systems control. MPC has the potential to replace involved control architectures, such as cascaded loops, by a unique controller. MPC formulations can be extended to suit specific modes of operation, e.g., start-up procedures and fault accommodation. Various embodiments of MPC principles have emerged as promising alternatives for power electronics. Successful designs however, require domain specific knowledge.

Outcomes

  • Elaboration of design guidelines for MPC with performance guarantees
  • Development of a fast algorithm for the direct control of power converters
  • MPC for switching between control with direct and with modulated actuation
  • MC for switching sequence direct power control of grid-connected power converters
  • Reference design for MPC of Active Front End rectifiers

Key features and advantages

The algorithms developed can be implemented in real-time and

  • provide performance guarantees
  • give enhanced trade-offs between transient and stead state response
  • enable the tracking of references for active and reactive power

Further reading (selection):

  • Quevedo and Geyer, “Model Predictive Control with Reference Tracking ” EP2725706A1, US9705420B2, JP2015532586A, KR20150074140A, CN201380055443, W02014064141A11, …
  • Quevedo, Aguilera and Geyer, “Predictive Control in Power Electronics and Drives: basic concepts, theory and methods,” in Advanced and Intelligent Control in Power Electronics and Drives, Springer, 2014
  • Aguilera, Lezana and Quevedo, “Switched Model Predictive Control for Improved Transient and Steady-State Performance,” IEEE Transactions on Industrial Informatics, Aug. 2015
  • Vazquez, Marquez, Aguilera, Quevedo, Leon and Franquelo, “Predictive Optimal Switching Sequence Direct Power Control for Grid Connected Power Converters,” IEEE Transactions on Industrial Electronics. Apr. 2015
  • Aguilera and Quevedo, “Predictive Control of Power Converters: Designs with Guaranteed Performance,” IEEE Transactions on Industrial Informatics, Feb. 2015
  • Geyer and Quevedo, “Multistep Finite Control Set Model Predictive Control for Power Electronics,” IEEE Transactions on Power Electronics, Dec. 2014.
  • Aguilera and Quevedo, “Stability Analysis of Quadratic MPC with a Discrete Input Alphabet,” IEEE Transactions on Automatic Control, Dec. 2013
  • Quevedo, Aguilera, Perez, Cortes, and Lizana “Model Predictive Control of an AFE Rectifier with Dynamic References ” IEEE Transactions on Power Electronics, July 2012.

Team

Funding

Amount: $335k AUD

Duration: 2011-2013

Source:

  • Australian Research Council (Discovery Program)

Other Team Members

Graham Goodwin (The University of Newcastle), Tobias Gever (ABB Corporate Research, Switzerland), Patricio Lezana, José Rodríguez, Patricio Cortés (Universidad Técnica Federico Santa María, Chile).