Tuning of multivariable model predictive controllers through expert bandit feedback
Alex S Ira, Chris Manzie, Iman Shames, Robert Chin, Dragan Nesic, Hayato Nakada, Takeshi Sano
International Journal of Control | Taylor & Francis | Published : 2020
For certain industrial control applications an explicit function capturing the non-trivial trade-off between competing objectives in closed loop performance is not available. In such scenarios it is common practice to use the human innate ability to implicitly learn such a relationship and manually tune the corresponding controller to achieve the desirable closed loop performance. This approach has its deficiencies because of individual variations due to experience levels and preferences in the absence of an explicit calibration metric. Moreover, as the complexity of the underlying system and/or the controller increase, in the effort to achieve better performance, so does the tuning time and..View full abstract
Related Projects (1)
Awarded by Australian Research Council
This work was supported by Australian Research Council [LP160100650].