dc dc buck converter for Model predictive control

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Mohamed
Mohamed 2019-8-29
回答： Chandrakanth Pavanaskar 2022-7-14
I have designed a dc dc buck converter for the Model predictive control, but when I run the code give the right numrical output but hte graphs are not acuret, any budy can help me to fix this problem
thank you
  2 个评论
Chandrakanth Pavanaskar
Chandrakanth Pavanaskar 2022-7-13
Hello,
I just saw your model, can I know how did you get the solution as the solution seems infeasible
Sam Chak
Sam Chak 2022-7-13
Ran in:
@Chandrakanth Pavanaskar
I'm unsure, but from the mathematical perspective, the system looks 'manipulatable' with numbers without using MPC. What is the purpose of having the MPC in this case?
Vg = 15; D = 0.4; L = 2e-3; C = 10e-6; R = 100;
a = [0 -(1-D)/L; (1-D)/C -1/(R*C)];
b = [1/L 0; 0 -1/C];
c = eye(length(a));
d = [0];
sys = ss(a, b, c, d); % System in state-space model
k1 = 1;
k2 = 1;
k = [-k1/500 3/5; 0.6 (k2 - 1e3)/1e5] % Gain Matrix
k = 2×2
-0.0020 0.6000 0.6000 -0.0100
br = diag([k1/500, -k2/1e5])*b; % Rescaled Reference Input Matrix
CLsys = ss(a+b*k, br, c, d) % Closed-loop system
CLsys = A = x1 x2 x1 -1 0 x2 7.276e-12 -1 B = u1 u2 x1 1 0 x2 0 1 C = x1 x2 y1 1 0 y2 0 1 D = u1 u2 y1 0 0 y2 0 0 Continuous-time state-space model.
step(CLsys) % Closed-loop step response

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回答（1 个）

Chandrakanth Pavanaskar
Hello,
Can I know the research material for this MPC design of buck converter?
Thank you

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