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Commitb10a823

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Balred() now will return a vector of reduced models if orders is passed as a vector.
1 parentf9584cd commitb10a823

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+76
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‎control/modelsimp.py

Lines changed: 76 additions & 60 deletions
Original file line numberDiff line numberDiff line change
@@ -233,7 +233,7 @@ def balred(sys, orders, method='truncate'):
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234234
Examples
235235
--------
236-
>>> rsys = balred(sys,order, method='truncate')
236+
>>> rsys = balred(sys,orders, method='truncate')
237237
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"""
239239
ifmethod=='matchdc':
@@ -257,73 +257,89 @@ def balred(sys, orders, method='truncate'):
257257
# else:
258258
dico='C'
259259

260+
rsys= []#empty list for reduced systems
261+
262+
#check if orders is a list or a scalar
263+
try:
264+
order=iter(orders)
265+
exceptTypeError:#if orders is a scalar
266+
orders= [orders]
267+
260268
#first get original system order
261269
nn=sys.A.shape[0]#no. of states
262270
mm=sys.B.shape[1]#no. of inputs
263271
rr=sys.C.shape[0]#no. of outputs
264272
#first do the schur decomposition
265273
T,V,l=schur(sys.A,sort='lhp')#l will contain the number of eigenvalues in the open left half plane, i.e. no. of stable eigenvalues
266274

267-
rorder=orders- (nn-l)
268-
ifrorder<=0:
269-
raiseValueError("System has %i unstable states which is more than ORDER(%i)"% (nn-l,orders))
270-
271-
ifl>0:#handles the stable/unstable decomposition if unstable eigenvalues are found
272-
#Author: M. Clement (mdclemen@eng.ucsd.edu) 2016
273-
print("Unstable eigenvalues found, performing stable/unstable decomposition")
274-
As=np.asmatrix(T)
275-
Bs=V.T*sys.B
276-
Cs=sys.C*V
277-
#from ref 1 eq(1) As = [A_ Ac], Bs = [B_], and Cs = [C_ C+]; _ denotes stable subsystem
278-
# [0 A+] [B+]
279-
A_=As[0:l,0:l]
280-
Ac=As[0:l,l::]
281-
Ap=As[l::,l::]
282-
283-
B_=Bs[0:l,:]
284-
Bp=Bs[l::,:]
285-
286-
C_=Cs[:,0:l]
287-
Cp=Cs[:,l::]
288-
#do some more tricky math IAW ref 1 eq(3)
289-
B_tilde=np.bmat([[B_,Ac]])
290-
D_tilde=np.bmat([[np.zeros((rr,mm)),Cp]])
291-
292-
subSys=StateSpace(A_,B_tilde,C_,D_tilde)
293-
294-
job='B'# balanced (B) or not (N)
295-
equil='N'# scale (S) or not (N)
296-
n=np.size(subSys.A,0)
297-
m=np.size(subSys.B,1)
298-
p=np.size(subSys.C,0)
299-
Nr,Ar,Br,Cr,hsv=ab09ad(dico,job,equil,n,m,p,subSys.A,subSys.B,subSys.C,nr=rorder,tol=0.0)
300-
301-
rsubSys=StateSpace(Ar,Br,Cr,np.zeros((p,m)))
302-
303-
A_r=rsubSys.A
304-
#IAW ref 1 eq(4) B^{tilde}_r = [B_r, Acr]
305-
B_r=rsubSys.B[:,0:mm]
306-
Acr=rsubSys.B[:,mm:mm+(nn-l)]
307-
C_r=rsubSys.C
308-
309-
#now put the unstable subsystem back in
310-
Ar=np.bmat([[A_r,Acr], [np.zeros((nn-l,rorder)),Ap]])
311-
Br=np.bmat([[B_r], [Bp]])
312-
Cr=np.bmat([[C_r,Cp]])
313-
314-
rsys=StateSpace(Ar,Br,Cr,sys.D)
315-
275+
foriinorders:
276+
rorder=i- (nn-l)
277+
ifrorder<=0:
278+
raiseValueError("System has %i unstable states which is more than ORDER(%i)"% (nn-l,i))
279+
280+
foriinorders:
281+
ifl>0:#handles the stable/unstable decomposition if unstable eigenvalues are found
282+
#Author: M. Clement (mdclemen@eng.ucsd.edu) 2016
283+
print("Unstable eigenvalues found, performing stable/unstable decomposition")
284+
rorder=i- (nn-l)
285+
As=np.asmatrix(T)
286+
Bs=V.T*sys.B
287+
Cs=sys.C*V
288+
#from ref 1 eq(1) As = [A_ Ac], Bs = [B_], and Cs = [C_ C+]; _ denotes stable subsystem
289+
# [0 A+] [B+]
290+
A_=As[0:l,0:l]
291+
Ac=As[0:l,l::]
292+
Ap=As[l::,l::]
293+
294+
B_=Bs[0:l,:]
295+
Bp=Bs[l::,:]
296+
297+
C_=Cs[:,0:l]
298+
Cp=Cs[:,l::]
299+
#do some more tricky math IAW ref 1 eq(3)
300+
B_tilde=np.bmat([[B_,Ac]])
301+
D_tilde=np.bmat([[np.zeros((rr,mm)),Cp]])
302+
303+
subSys=StateSpace(A_,B_tilde,C_,D_tilde)
304+
305+
job='B'# balanced (B) or not (N)
306+
equil='N'# scale (S) or not (N)
307+
n=np.size(subSys.A,0)
308+
m=np.size(subSys.B,1)
309+
p=np.size(subSys.C,0)
310+
Nr,Ar,Br,Cr,hsv=ab09ad(dico,job,equil,n,m,p,subSys.A,subSys.B,subSys.C,nr=rorder,tol=0.0)
311+
312+
rsubSys=StateSpace(Ar,Br,Cr,np.zeros((p,m)))
313+
314+
A_r=rsubSys.A
315+
#IAW ref 1 eq(4) B^{tilde}_r = [B_r, Acr]
316+
B_r=rsubSys.B[:,0:mm]
317+
Acr=rsubSys.B[:,mm:mm+(nn-l)]
318+
C_r=rsubSys.C
319+
320+
#now put the unstable subsystem back in
321+
Ar=np.bmat([[A_r,Acr], [np.zeros((nn-l,rorder)),Ap]])
322+
Br=np.bmat([[B_r], [Bp]])
323+
Cr=np.bmat([[C_r,Cp]])
324+
325+
rsys.append(StateSpace(Ar,Br,Cr,sys.D))
326+
327+
else:
328+
job='B'# balanced (B) or not (N)
329+
equil='N'# scale (S) or not (N)
330+
n=np.size(sys.A,0)
331+
m=np.size(sys.B,1)
332+
p=np.size(sys.C,0)
333+
Nr,Ar,Br,Cr,hsv=ab09ad(dico,job,equil,n,m,p,sys.A,sys.B,sys.C,nr=i,tol=0.0)
334+
335+
rsys.append(StateSpace(Ar,Br,Cr,sys.D))
336+
337+
#if orders was a scalar, just return the single reduced model, not a list
338+
iflen(orders)==1:
339+
returnrsys[0]
340+
#if orders was a list/vector, return a list/vector of systems
316341
else:
317-
job='B'# balanced (B) or not (N)
318-
equil='N'# scale (S) or not (N)
319-
n=np.size(sys.A,0)
320-
m=np.size(sys.B,1)
321-
p=np.size(sys.C,0)
322-
Nr,Ar,Br,Cr,hsv=ab09ad(dico,job,equil,n,m,p,sys.A,sys.B,sys.C,nr=orders,tol=0.0)
323-
324-
rsys=StateSpace(Ar,Br,Cr,sys.D)
325-
326-
returnrsys
342+
returnrsys
327343

328344
defminreal(sys,tol=None,verbose=True):
329345
'''

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