MATLAB MODEL PREDICTIVE CONTROL TOOLBOX - S Spécifications télécharger pdf (Page 76)

3 Designing Controllers Using the Design Tool GUI

3-26

Improved Setpoint Tracking for CSTR Temperature

On the other hand, the reactant concentration, C

, exhibits a larger deviation from its

setpoint, which is being held constant at zero (compare to Plant Outputs for T Setpoint

Scenario with Added Data Markers, where the final deviation is about a factor of 4

smaller).

This behavior reflects an unavoidable trade-off. The controller has only one adjustment

at its disposal: the coolant temperature. Therefore, it can't satisfy setpoints on both

outputs.

Output Weights

The output weights let you dictate the accuracy with which each output must track

its setpoint. Specifically, the controller predicts deviations for each output over the

prediction horizon. It multiplies each deviation by the output's weight value, and then

computes the weighted sum of squared deviations, S

(k), as follows

S k w r k i y k i

j j j

P y

( ) [ ( ) ( )]= + - +

{ }

ÂÂ

where k is the current sampling interval, k + i is a future sampling interval (within the

prediction horizon), P is the number of control intervals in the prediction horizon, n

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MATLAB MODEL PREDICTIVE CONTROL TOOLBOX - S Spécifications Page 76