Specifications

Design Controller Using the Design Tool
3-29
S k w u k i u
u j
u
j j
j
n
i
M
mv
( ) [ ( ) ]= + - -
{ }
==
ÂÂ
1
2
11
where w
u
j
is the input weight and
u
j
is the nominal value for input j. In the above
simulations, you used the default, w
u
j
= 0. This is the usual choice.
When a sustained disturbance or setpoint change occurs, the manipulated variable must
deviate permanently from its nominal value (as shown in Plant Inputs for the T Setpoint
Scenario and Plant Inputs for Modified Rate Weight). Using a nonzero input weight
forces the corresponding input back toward its nominal value. Test this by running
a simulation in which you set the input weight to 1. The final T
c
value is closer to its
nominal value, but this causes T to deviate from the new setpoint (not shown).
Note Some applications involve more manipulated variables than plant outputs. In such
cases, it is common to define nonzero input weights on certain manipulated variables
in order to hold them near their most economical values. The remaining manipulated
variables eliminate steady-state error in the plant outputs.
Blocking
The section “Weight Tuning” on page 3-24 used penalty weights to shape the
controller's response. This section covers the following topics:
• An alternative to penalty weighting, called blocking
• Side-by-side controller comparisons
To begin, select Controllers in the tree, and click the New button, creating a controller
initialized to the Model Predictive Control Toolbox default settings. Rename this
controller Blocking1 by editing the appropriate table cell.
Select Blocking 1 in the tree, select its Weight Tuning tab, and set the Weight for
output C_A to 0 (see “Weight Tuning” on page 3-24 to review the reason for this).
Leave other weights at their defaults.
Now select the Model and Horizons tab, and select its Blocking check box. This
activates the blocking options. It also deactivates the Control Horizon option (the
blocking options override it).