@article{WanYouGawTay09,
  author = {Wang, Liuping
		and Young, Peter C.
		and Gawthrop, Peter J.
		and Taylor, C. James},
  title = {Non-minimal state-space model-based continuous-time model predictive control with constraints},
  journal = {International Journal of Control},
  year = 2009,
  volume = 82,
  issue = 6,
  pages = {1122--1137},
  publisher = {Taylor and Francis},
  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.},
  issn = {0020-7179},
  doi = {10.1080/00207170802474694},
  note = {Published online 16 March 2009}
}

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