Self-tuning control based on penalized least squares identification techniques

In self-tuning control problems, the parameter estimate can exhibit undesirable behaviors due to the possible lack of information in some directions of the parameter space. In this contribution, a penalized technique able to enforce certain desired properties to the estimates is introduced. Its usefulness in an adaptive control context is also discussed