# Documentation

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# tf2ss

Convert transfer function filter parameters to state-space form

## Syntax

[A,B,C,D] = tf2ss(b,a)

## Description

tf2ss converts the parameters of a transfer function representation of a given system to those of an equivalent state-space representation.

[A,B,C,D] = tf2ss(b,a) returns the A, B, C, and D matrices of a state space representation for the single-input transfer function

$H\left(s\right)=\frac{B\left(s\right)}{A\left(s\right)}=\frac{{b}_{1}{s}^{n-1}+\cdots +{b}_{n-1}s+{b}_{n}}{{a}_{1}{s}^{m-1}+\cdots +{a}_{m-1}s+{a}_{m}}=C{\left(sI-A\right)}^{-1}B+D$

in controller canonical form

$\begin{array}{l}\stackrel{˙}{x}=Ax+Bu\\ y=Cx+Du\end{array}$

The input vector a contains the denominator coefficients in descending powers of s. The rows of the matrix b contain the vectors of numerator coefficients (each row corresponds to an output). In the discrete-time case, you must supply b and a to correspond to the numerator and denominator polynomials with coefficients in descending powers of z.

For discrete-time systems you must make b have the same number of columns as the length of a. You can do this by padding each numerator represented in b (and possibly the denominator represented in the vector a) with trailing zeros. You can use the function eqtflength to accomplish this if b and a are vectors of unequal lengths.

The tf2ss function is part of the standard MATLAB® language.

 Note   There is disagreement in the literature on naming conventions for the canonical forms. It is easy, however, to generate similarity transformations that convert these results to other forms.

## Examples

collapse all

Consider the system described by the transfer function

 

Convert it to state-space form using tf2ss.

b = [0 2 3; 1 2 1]; a = [1 0.4 1]; [A,B,C,D] = tf2ss(b,a) 
A = -0.4000 -1.0000 1.0000 0 B = 1 0 C = 2.0000 3.0000 1.6000 0 D = 0 1 

A one-dimensional discrete-time oscillating system consists of a unit mass, , attached to a wall by a spring of unit elastic constant. A sensor samples the acceleration, , of the mass at Hz.

Generate 50 time samples. Define the sampling interval .

Fs = 5; dt = 1/Fs; N = 50; t = dt*(0:N-1); u = [1 zeros(1,N-1)]; 

The transfer function of the system has an analytic expression:

 

The system is excited with a unit impulse in the positive direction. Compute the time evolution of the system using the transfer function. Plot the response.

bf = [1 -(1+cos(dt)) cos(dt)]; af = [1 -2*cos(dt) 1]; yf = filter(bf,af,u); stem(t,yf,'o') xlabel('t') 

Find the state-space representation of the system. Compute the time evolution starting from an all-zero initial state. Compare it to the transfer-function prediction.

[A,B,C,D] = tf2ss(bf,af); x = [0;0]; for k = 1:N y(k) = C*x + D*u(k); x = A*x + B*u(k); end hold on stem(t,y,'*') hold off legend('tf','ss')