Documentation

This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Control of a Single-Input-Single-Output Plant

This example shows how to control a double integrator plant under input saturation in Simulink®.

Define Plant Model

The linear open-loop dynamic model is a double integrator:

plant = tf(1,[1 0 0]);

Design MPC Controller

Create the controller object with sampling period, prediction and control horizons:

Ts = 0.1;
p = 10;
m = 3;
mpcobj = mpc(plant, Ts, p, m);
-->The "Weights.ManipulatedVariables" property of "mpc" object is empty. Assuming default 0.00000.
-->The "Weights.ManipulatedVariablesRate" property of "mpc" object is empty. Assuming default 0.10000.
-->The "Weights.OutputVariables" property of "mpc" object is empty. Assuming default 1.00000.

Specify actuator saturation limits as MV constraints.

mpcobj.MV = struct('Min',-1,'Max',1);

Simulate Using Simulink®

To run this example, Simulink® is required.

if ~mpcchecktoolboxinstalled('simulink')
    disp('Simulink(R) is required to run this example.')
    return
end

Simulate closed-loop control of the linear plant model in Simulink. Controller "mpcobj" is specified in the block dialog.

mdl = 'mpc_doubleint';
open_system(mdl);
sim(mdl);
-->Converting the "Model.Plant" property of "mpc" object to state-space.
-->Converting model to discrete time.
   Assuming no disturbance added to measured output channel #1.
-->The "Model.Noise" property of the "mpc" object is empty. Assuming white noise on each measured output channel.

The closed-loop response shows good setpoint tracking performance.

bdclose(mdl)
Was this topic helpful?