DOI: 10.3724/SP.J.1219.2013.00742

Information and Control (信息与控制) 2013/42:6 PP.742-749

Robust Model Predictive Control Based on Online Optimization

The robust model prediction algorithm based on linear matrix inequality breaks into two parts- online and offline. In order to improve the response speed and control accuracy of system, the upper bound of objective function obtained by offline algorithm is set as a known parameter and reoptimization is carried out to get a sequence of asymptotically stable invariant ellipsoid sets. The state variables can be determined-lying between two ellipsoid sets within the ellipsoid set sequence, on the basis of online measured state variables. The state variables can be accurately located and the system control variable can be obtained by adding an adjacent small elliptical set and optimizing with three ellipsoid sets. The online optimization is theoretically proved. Simulation results indicate that the control effect of the proposed algorithm is better than conventional algorithms. Taking fan control system in variable air volume (VAV) air-conditioning system as an example, the results verify the effectiveness of the proposed algorithm.

Key words:model predictive control,linear matrix inequality,robust,online optimization

ReleaseDate:2015-04-15 18:52:44

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