sw = 0
for i in range(len(pw)):
error = pw[i] - sw
u = pid.run(error, Ts=Ts)
sw = dc2.dlsim(u)[0]
y_out[i, :] = sw
pylab.figure(2)
pylab.plot(pw)
pylab.plot(y_out[:, 0])
#Clearing the previous states
dc2.x0 = None
sinW = sinwave(Ts=Ts, mtime=1, freq=1, amp=6000)
pw = sinW.signal()
y_out = zeros((len(pw), 1))
u_out = zeros((len(pw), 1))
sw = 0
for i in range(len(pw)):
error = pw[i] - sw
u = pid.run(error, Ts=Ts)
sw = dc2.dlsim(u)[0]
y_out[i, :] = sw
u_out[i, :] = u
pylab.figure(3)
pylab.plot(pw)
pylab.plot(y_out[:, 0])
#
# for i in range( len( mtime ) ):
# u = array( [[200.], [2.]] )
# yo[i, :] = pmsm.dlsim( u, Ts = Ts )[1][:, 0]
# if( i % 1000 ) == 0:
# print "%d of %d" % ( i, len( mtime ) )
#
# pylab.figure()
# pylab.plot( yo[:, 2] )
#
# pylab.show()
#Control signals
# squareW = squarewave( Ts = Ts, mtime = 10 , freq = 0.2, amp = 30 )
# sw = squareW.signal()
sinW = sinwave( Ts = Ts, mtime = 1, freq = 2, amp = 30 )
sw = sinW.signal()
ct = CT()
#Number of horizon
N = 2
( Ak, Bk, Ck, Dk ) = pmsm.mdss( x, Ts )
dlqr = DSTLQR( Ak, Bk, Ck, N )
w_s = zeros( ( len( sw ), 1 ) )
U_s = zeros( ( len( sw ), 2 ) )
x_s = zeros( ( len( sw ), 5 ) )
error = zeros( ( len( sw ), 1 ) )
w_est = zeros( ( len( sw ), 1 ) )
if __name__ == "__main__":
dc2 = dcmotor()
Ts = 0.0001
ekf = dKF(x0=zeros((3, 1)))
mtime = arange(0, 0.01, Ts)
yo = zeros((len(mtime), 1))
xk = zeros((len(mtime), 3))
xe = zeros((len(mtime), 3))
noise = zeros((len(mtime), 3))
error = zeros((len(mtime), 3))
(A, B, C, D) = dc2.dss(Ts)
sinW = sinwave(Ts=Ts, mtime=0.01, freq=100, amp=20)
pw = sinW.signal()
H = array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
for i in range(len(mtime)):
u = pw[i]
# u = array([[1.]])
y_k, x_k = dc2.dlsim(u, Ts=Ts);
yo[i, :] = y_k
xk[i, :] = x_k.conj().T
z_K = copy(x_k)
z_K[1] = 0
z_K[0] = z_K[0] + random.uniform(-0.5, 0.5)
if __name__ == "__main__":
dc2 = dcmotor()
Ts = 0.0001
ekf = dKF(x0=zeros((3, 1)))
mtime = arange(0, 0.01, Ts)
yo = zeros((len(mtime), 1))
xk = zeros((len(mtime), 3))
xe = zeros((len(mtime), 3))
noise = zeros((len(mtime), 3))
error = zeros((len(mtime), 3))
(A, B, C, D) = dc2.dss(Ts)
sinW = sinwave(Ts=Ts, mtime=0.01, freq=100, amp=20)
pw = sinW.signal()
H = array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
for i in range(len(mtime)):
u = pw[i]
#u = array([[1.]])
y_k, x_k = dc2.dlsim(u, Ts=Ts)
yo[i, :] = y_k
xk[i, :] = x_k.conj().T
z_K = copy(x_k)
z_K[1] = 0
z_K[0] = z_K[0] + random.uniform(-0.5, 0.5)
for i in range( len( mtime ) ): u = array( [1.] ) yo[i, :] = dc2.dlsim( u, 0, Ts = Ts )[0]; pylab.plot( yo[:, 0] ) #------------------------------------------------------------------------------ # DC motor PID controller #------------------------------------------------------------------------------ # Clearing the previous states dc2.x0 = None; sinW = sinwave( Ts = Ts, mtime = 0.1, freq = 10, amp = 200 ) pw = sinW.signal() # Defining the torque torque = concatenate( ( ones( ( 1, pw.shape[0] / 4 ) ) * 2.0, ones( ( 1, 3 * pw.shape[0] / 4 ) ) * 1.0 ), axis = 1 ); y_out = zeros( ( len( pw ), 1 ) ) u_out = zeros( ( len( pw ), 1 ) ) sw = 0; for i in range( len( pw ) ): # Calculate the error error = pw[i] - sw; # Calculating the control signal u = pid.run( error, Ts = Ts ) if( abs( u ) > 220 ): u = sign( u ) * 220;
for i in range( len( pw ) ): error = pw[i] - sw; u = pid.run( error, Ts = Ts ) sw = dc2.dlsim( u )[0]; y_out[i, :] = sw pylab.figure( 2 ) pylab.plot( pw ) pylab.plot( y_out[:, 0] ) #Clearing the previous states dc2.x0 = None; sinW = sinwave( Ts = Ts, mtime = 1, freq = 1, amp = 6000 ) pw = sinW.signal() y_out = zeros( ( len( pw ), 1 ) ) u_out = zeros( ( len( pw ), 1 ) ) sw = 0; for i in range( len( pw ) ): error = pw[i] - sw; u = pid.run( error, Ts = Ts ) sw = dc2.dlsim( u )[0]; y_out[i, :] = sw u_out[i, :] = u pylab.figure( 3 ) pylab.plot( pw )
