pole placement in M-file
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hello every one ... how can i determine (p) in pole placement code K = place(A,B,p)
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Shashank Prasanna
2013년 7월 20일
shahad, place is used to perform pole placement using state feedback. The output K is the feedback gain matrix.
PLACE is not an optimal control methodology and does no come up with good p values. It merely attempts to place at the specified location and generates the gain matrix.
You question seems to be related to: How do I generate this stable optimal p?
There are numerous answers to that question but a popular one is linear quadratic controller (LQR):
The first output argument is the gain matrix K and the 3rd output argument 'e' are you poles which are automatically generated when the optimization is performed.
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Azzi Abdelmalek
2013년 8월 16일
Shashank, What I mean by optimal poles is poles that provide a system optimal performances (acceptable stability margin, and optimal performances to be defined by the user).
Azzi Abdelmalek
2013년 7월 20일
편집: Azzi Abdelmalek
2013년 7월 20일
p is the poles vector you have to impose to your system in closed loop.
Example:
A=[-6 -5;1 0];
b=[1;0]
The size of A is 2x2 then the length of the pole vector p should be 2
p=[-5 -10] % the poles should be stables (real(p)<0)
%or
p=[-2+j -2-j]
place(A,b,p)
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Azzi Abdelmalek
2013년 7월 20일
Like I said the pole to impose should be real or complex numbers with real part obligatory negative. This is enough to get a stable control, for optimal performances, you have to read the effects of poles on the system.
Nagesh
2024년 3월 1일
A=[-6 -5;1 0];
b=[1;0]
p=[-5 -10] % the poles should be stables (real(p)<0)
%or
p=[-2+j -2-j]
place(A,b,p)
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Sam Chak
2024년 3월 1일
Hi @Nagesh
Your response didn't fully address the original question. In order to determine the control gain using the place() command, the user must input the poles that result in the Hurwitz characteristic polynomial. These poles specifically correspond to the closed-loop system and generate the desired response specified by the user. Your answer deserves votes if you could provide a practical example to illustrate this.
Let's consider a simple Double Integrator system. If we need to meet performance specifications such as a percent overshoot of ≤ 9% and a settling time of ≤ 1 second, how would you determine the target poles?
A = [0, 1; 0, 0]; % state matrix
B = [0; 1]; % input matrix
C = [1, 0]; % output matrix
D = 0*C*B; % direct matrix
sys = ss(A, B, C, D)
Gp = tf(sys)
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