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A nonlinear predictive generalized minimum variance (NPGMV) control algorithm is introduced for the control of nonlinear multivariable systems. The plant model is represented by a series combination of a nonlinear operator, which is assumed finite-gain stable, and a linear state-space model, which can include time delays and unstable modes. The main contribution is to incorporate predictive action into the recently introduced Nonlinear GMV controller by defining a multi-step cost index and using a minimum-variance form of the usual GPC cost function. The solution is very different to traditional nonlinear model predictive control, providing a solution which is similar to fixed model based controllers. This does not provide the same constrained optimization features but it does give a controller which is very simple to implement.
|Title of host publication||American Control Conference, 2008|
|Number of pages||5|
|Publication status||Published - Jun 2008|
|Event||2008 American Control Conference - Seattle, United States|
Duration: 11 Jun 2008 → 13 Jun 2008
|Conference||2008 American Control Conference|
|Period||11/06/08 → 13/06/08|
- multivariable control systems
- nonlinear control systems
- predictive control
FingerprintDive into the research topics of 'Non-linear predictive GMV control'. Together they form a unique fingerprint.
- 1 Finished
Grimble, M., Katebi, R. & Ordys, A.
1/05/05 → 30/04/10