| Model Predictive Control Toolbox | |
Adds one or more unmeasured disturbances to a plant model in MPC mod format. Used for simulation of disturbances and for design of state estimators in MPC.
Syntax
Description
The disturbance model contained in dmod adds to the plant model contained in pmod to form a composite, model, with the structure given in the following block diagram:
pmod, dmod and model are in the MPC mod format (see mod in the online MATLAB Function Reference for a detailed description). You would normally create pmod and dmod using either the tfd2mod, ss2mod or th2mod functions.
addumd is a specialized version of paramod. Its main advantage over paramod is that it assumes all the inputs to dmod are to be unmeasured disturbances. This saves you the trouble of designating the input types in a separate step.
Example
See ss2mod for an example of the use of this function.
Algorithm
addumd converts pmod and dmod into their state-space form, then uses the mpcparal function to build the composite model.
Restrictions
pmod and dmod must have been created with equal sampling periods and number of output variables.
pmod must not include unmeasured disturbances, i.e., its mod format must specify nw = 0.
dmod must be classified as manipulated variables. (They will be reclassified automatically as unmeasured disturbances in model.) So the mod format of dmod must specify nd = nw = 0 (which is the default for all model creation functions).
See Also
addmod, addmd, appmod, paramod, sermod, smpcest
| addmod | appmod | |