MATLAB MODEL PREDICTIVE CONTROL TOOLBOX - S Spécifications télécharger pdf (Page 126)

4 Designing Controllers Using the Command Line

4-16

Animation of the Multi-Model Example

In order to achieve its objective, the controller can adjust the applied force magnitude

(the length of the red arrow). It receives continuous feedback on the M

location. There is

also a contact sensor to signal collisions. The M

location is unmeasured.

If M

were isolated, this would be a routine control problem. The challenge is that the

relationship between the applied force and the M

movement changes dramatically when

attaches to M

The following code defines the model. First define the system parameters as follows:

%% Model Parameters

M1=1; % mass

M2=5; % mass

k1=1; % spring constant

k2=0.1; % spring constant

b1=0.3; % friction coefficient

b2=0.8; % friction coefficient

yeq1=10; % wall mount position

yeq2=-10; % wall mount position

Next define a model of M

when the masses are separated. Its states are the M

position

and velocity. Its inputs are the applied force, which will be the controller's manipulated

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MATLAB MODEL PREDICTIVE CONTROL TOOLBOX - S Spécifications Page 126