Wang, L., Young, P.C., Gawthrop, P.J. and Taylor, J. (2009) Non-minimal state-space model-based continuous-time model predictive control with constraints. International Journal of Control, 82(6), pp. 1122-1137. (doi: 10.1080/00207170802474694)
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Abstract
This article proposes a model predictive control scheme based on a non-minimal state-space (NMSS) structure. Such a combination yields a continuous-time state-space model predictive control system that permits hard constraints to be imposed on both plant input and output variables, whilst using NMSS output-feedback without the need for an observer. A comparison between the NMSS and observer-based approaches using Monte Carlo uncertainty analysis shows that the former design is considerably less sensitive to plant-model mismatch than the latter. Through simulation studies, the article also investigates the role of the implementation filter in noise attenuation, disturbance rejection and robustness of the closed-loop predictive control system. The results show that the filter poles become a subset of the closed-loop poles and this provides a straightforward method of tuning the closed-loop performance to achieve a reasonable balance between speed of response, disturbance rejection, measurement noise attenuation and robustness.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Gawthrop, Professor Peter |
| Authors: | Wang, L., Young, P.C., Gawthrop, P.J., and Taylor, J. |
| College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | International Journal of Control |
| ISSN: | 0020-7179 |
| Published Online: | 16 March 2009 |
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