Predictive control of switching power converters

Predictive controllers rely on optimum control systems theory and aim to solve a cost function minimization problem.[1][2] Predictive controllers are relatively easy to numerically implement but electronic power converters are non-linear time-varying dynamic systems, so a different approach to predictive must be taken.

Principles of non-linear predictive optimum control

The first step to designing a predictive controller is to derive a detailed direct dynamic model (including non-linearities) of the switching power converter. This model must contain enough detail of the converter dynamics to allow, from initial conditions, a forecast in real time and with negligible error, of the future behavior of the converter.

Sliding mode control of switching power converters chooses a vector to reach sliding mode as fast as possible (high switching frequency).

It would be better to choose a vector to ensure zero error at the end of the sampling period Δt.To find such a vector, a previous calculation can be made (prediction);

The converter has a finite number of vectors (states) and is usually non-linear: one way is to try all vectors to find the one that minimizes the control errors, prior to the application of that vector to the converter.

  • Direct dynamics model-based predictive control (DDMBPC)
Direct Dynamics Predictive Control of Switching Power Converters
  • Inverse dynamics optimum predictive control (IDOPC)
Inverse Dynamics Predictive Control of Switching Power Converters

References
  1. Levine, W. S. ed. The Control Handbook, CRC/IEEE Press, Boca Raton, USA, 1996.
  2. M. Athans, Lecture Notes on Design of Robust Multivariable Feedback Control System, Prof. of Electrical Engineering, MIT, Visiting Research Emeritus Prof ISR/IST, Lisboa, 2004
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.