system_modeling Namespace Reference

Functions
def	plot_plat_sim (sim_time, sim_result, title, fig_size)
	Th function creates an appropriately formatted system test plot. More...

Variables
	A = np.asmatrix(np.loadtxt('A.txt',delimiter=','))
	State space system state matrix A. More...
	B = np.asmatrix(np.loadtxt('B.txt',delimiter=',')).transpose()
	State space system input matrix B. More...
	C = np.matrix()
	State space system state output matrix C. More...
int	D = 0
	State space system input output matrix D. More...
	sys = control.StateSpace(A,B,C,D)
	State space system object. More...
	TA = np.arange(0,1,.001)
	Simulation A time vector. More...
list	X0A = [0, 0, 0, 0]
	Simulation A initial conditions. More...
	RA = control.initial_response(sys,TA,X0A)
	Simulation A results. More...
	TB = np.arange(0,0.4,.001)
	Simulation B time vector. More...
list	X0B = [.05, 0, 0, 0]
	Simulation b initial conditions. More...
	RB = control.initial_response(sys,TB,X0B)
	Simulation B results. More...
	TC = np.arange(0,0.4,.001)
	Simulation C time vector. More...
list	X0C = [0.001619, 5*3.14159/180, 0, 0]
	Simulation C initial conditions. More...
	RC = control.initial_response(sys,TC,X0C)
	Simulation C results. More...
	TD = np.arange(0,0.4,.001)
	Simulation D time vector. More...
	u0D = np.zeros((1,len(TD)))
	Simulation D input signal. More...
list	X0D = [0, 0, 0, 0]
	Simulation D input signal. More...
	RD = control.forced_response(sys,TD,u0D,X0D)
	Simulation D results. More...
	K = np.matrix()
	Closed loop systems gain matrix. More...
	A_cl = np.subtract(A,np.matmul(B,K))
	Closed loop state space system state matrix. More...
	B_cl = np.matrix()
	Closed loop state space system input matrix set to zeros since the system is used as a regulator. More...
	sys_cl = control.StateSpace(A_cl,B_cl,C,D)
	Closed loop state space system object. More...
	TA_cl = np.arange(0,1,.001)
	Closed loop simulation A time vector. More...
list	X0A_cl = [0, 0, 0, 0]
	Closed loop simulation A initial conditions. More...
	RA_cl = control.initial_response(sys_cl,TA_cl,X0A_cl)
	Closed loop simulation A results. More...
	TB_cl = np.arange(0,20,.001)
	Closed loop simulation B time. More...
list	X0B_cl = [.05, 0, 0, 0]
	Closed loop simulation B initial conditions. More...
	RB_cl = control.initial_response(sys_cl,TB_cl,X0B_cl)
	Closed loop simulation B results. More...
	TC_cl = np.arange(0,20,.001)
	Closed loop simulation C time. More...
list	X0C_cl = [0.001619, 5*3.14159/180, 0, 0]
	Closed loop simulation C initial conditions. More...
	RC_cl = control.initial_response(sys_cl,TC_cl,X0C_cl)
	Closed loop simulation C results. More...

Function Documentation

plot_plat_sim()

def system_modeling.plot_plat_sim	(		sim_time,
			sim_result,
			title,
			fig_size
	)

Th function creates an appropriately formatted system test plot.

Parameters

sim_time	a vector containing the simulation time steps.
sim_results	a matrix with the system simulation output.
title	A str describing the plot.
fig_size	A tuple giving the width and height of the figure.

Variable Documentation

A

system_modeling.A = np.asmatrix(np.loadtxt('A.txt',delimiter=','))

State space system state matrix A.

A_cl

system_modeling.A_cl = np.subtract(A,np.matmul(B,K))

Closed loop state space system state matrix.

B

system_modeling.B = np.asmatrix(np.loadtxt('B.txt',delimiter=',')).transpose()

State space system input matrix B.

B_cl

system_modeling.B_cl = np.matrix()

Closed loop state space system input matrix set to zeros since the system is used as a regulator.

C

system_modeling.C = np.matrix()

State space system state output matrix C.

D

int system_modeling.D = 0

State space system input output matrix D.

K

system_modeling.K = np.matrix()

Closed loop systems gain matrix.

RA

system_modeling.RA = control.initial_response(sys,TA,X0A)

Simulation A results.

RA_cl

system_modeling.RA_cl = control.initial_response(sys_cl,TA_cl,X0A_cl)

Closed loop simulation A results.

RB

system_modeling.RB = control.initial_response(sys,TB,X0B)

Simulation B results.

RB_cl

system_modeling.RB_cl = control.initial_response(sys_cl,TB_cl,X0B_cl)

Closed loop simulation B results.

RC

system_modeling.RC = control.initial_response(sys,TC,X0C)

Simulation C results.

RC_cl

system_modeling.RC_cl = control.initial_response(sys_cl,TC_cl,X0C_cl)

Closed loop simulation C results.

RD

system_modeling.RD = control.forced_response(sys,TD,u0D,X0D)

Simulation D results.

sys

system_modeling.sys = control.StateSpace(A,B,C,D)

State space system object.

sys_cl

system_modeling.sys_cl = control.StateSpace(A_cl,B_cl,C,D)

Closed loop state space system object.

TA

system_modeling.TA = np.arange(0,1,.001)

Simulation A time vector.

TA_cl

system_modeling.TA_cl = np.arange(0,1,.001)

Closed loop simulation A time vector.

TB

system_modeling.TB = np.arange(0,0.4,.001)

Simulation B time vector.

TB_cl

system_modeling.TB_cl = np.arange(0,20,.001)

Closed loop simulation B time.

TC

system_modeling.TC = np.arange(0,0.4,.001)

Simulation C time vector.

TC_cl

system_modeling.TC_cl = np.arange(0,20,.001)

Closed loop simulation C time.

TD

system_modeling.TD = np.arange(0,0.4,.001)

Simulation D time vector.

u0D

system_modeling.u0D = np.zeros((1,len(TD)))

Simulation D input signal.

X0A

list system_modeling.X0A = [0, 0, 0, 0]

Simulation A initial conditions.

X0A_cl

list system_modeling.X0A_cl = [0, 0, 0, 0]

Closed loop simulation A initial conditions.

X0B

list system_modeling.X0B = [.05, 0, 0, 0]

Simulation b initial conditions.

X0B_cl

list system_modeling.X0B_cl = [.05, 0, 0, 0]

Closed loop simulation B initial conditions.

X0C

list system_modeling.X0C = [0.001619, 5*3.14159/180, 0, 0]

Simulation C initial conditions.

X0C_cl

list system_modeling.X0C_cl = [0.001619, 5*3.14159/180, 0, 0]

Closed loop simulation C initial conditions.

X0D

list system_modeling.X0D = [0, 0, 0, 0]

Simulation D input signal.