How to include a model (created by me at Simulink) in Matlab script?
7 vues (au cours des 30 derniers jours)
jana nassereddine le 20 Mai 2023
so I have model predictive controller with a plant model, and I created the plant model using blogs, I couldn't use the state space representation because I have a disturbance acting on the system, so the only way to include it is by making the model with a blocks,
so anyway now i am writing a code for custom state estimation in script, and I need to mention the plant model I have used in this script, but when I write the name of the plant model or the name of the plant model with MPC, an error appears as
"error using mpc, the first input argument of the mpc command must be an LTI object or a structure of models and offsets"
so my question is how to include the model (I have created using block ) into my script?
% Custom State Estimation
xmpc = mpcstate(mpcobj);
A=[1 0;0 1];
B=[0.0936 0.0936 0;0 0.0752 0];
C=[1 0;0 1];
SOCpbref=75; % (en pourcentage)
SOCliref=85; % (en pourcentage)
t=25; % en seconds
Cmaxpb=22020; % As (Ampersecond)
Cmaxli=6000; % As (Ampersecond)
Ipb=[60 65 70 75 65 60 55 50 50 50 55 60 65 70 75 75 75 75 70 60 60 55 65 60 50]; % en Ampere
Ili=[70 75 80 85 75 70 65 60 60 60 65 70 75 80 85 85 85 85 80 70 70 65 75 70 60]; % en Ampere
for t = 0:Nc
y = sys.C*xsys; % plant equations: output
YY(t+1) = y;
xmpc.Plant = [SOCpb, SOCli]; % state estimation
u = mpcmove(mpcobj,xmpc,,[SOCpbref, SOCliref]); % y is not needed
UU(t+1) = u;
xsys = sys.A*xsys + sys.B*u; % plant equations: next state
Error using mpc
The first input argument of the "mpc" command must be an LTI object or a structure of models and offsets.
Error in customstateestimation (line 3)
Paul le 20 Mai 2023
Can you clarify this statement: "I couldn't use the state space representation because I have a disturbance acting on the system,"
The state space ss object can include all inputs to the system, i.e., control, disturbance, noise, etc.
Plus de réponses (1)
Emmanouil Tzorakoleftherakis le 23 Mai 2023
Currently you cannot use a Simulink model as prediction model for MPC design. This is something we are working towards for a future release. Since it seems you are designing a linear MPC controller, you could linearize your Simulink model at the desired operating point to get a linear representation, or you could use system identification as well if you are fine with a data-driven model. Here are a couple of examples:
Hope this helps