Loading...
Please wait, while we are loading the content...
Similar Documents
Identificação por meio do erro de predição aplicada ao projeto baseado em dados de controladores multivariáveis
| Content Provider | Semantic Scholar |
|---|---|
| Author | Huff, Daniel Denardi |
| Copyright Year | 2019 |
| Abstract | In this work, a data-driven control method – the Optimal Contr lle Identification (OCI) – is extended for multivariable systems. Based on a singl e batch of input-output data collected from the process, a fixed structure controlle r is stimated without using a process model, by embedding the control design problem in th e prediction error identification of an optimal controller. Even though the multiple-i nput multiple-output (MIMO) formulation is extended from its single-input single-outp ut (SISO) version in a natural way, the solution of the optimization problem is rather comp lex due to the special structure the inverse of the controller assumes in its MIMO versio n. A flexible formulation of the OCI method is also developed to cope with non-minimum ph ase (NMP) systems, withouta priori knowledge of the NMP transmission zero, which is identified a long with the controller parameters. A similar approach has already b een developed for the Virtual Reference Feedback Tuning (VRFT) method for diagonal referen c models. Here we consider not only diagonal but more general reference model str uctu es. Simulated results as well as an experiment on a level plant show the efficiency of th e proposed methodology, also comparing the OCI with the VRFT method. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://lume.ufrgs.br/bitstream/handle/10183/197208/001096794.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
