This example shows how to convert a discrete-time system to continuous time using d2c, and compares the results using two different interpolation methods.
Convert the second-order discrete-time system
to continuous time using the zero-order hold (ZOH) method.
G = zpk(-0.5,[-2,5],1,0.1); Gcz = d2c(G)
Warning: The model order was increased to handle real negative poles. > In warning at 26 In ssdata.utInvDiscretizeZOH at 74 In ssdata.d2c at 24 In zpkdata.d2c at 156 In SystemArray>SystemArray.d2c_ at 367 In zpk.zpk>zpk.d2c_ at 823 In DynamicSystem.d2c at 69 Gcz = 2.6663 (s^2 + 14.28s + 780.9) ------------------------------- (s-16.09) (s^2 - 13.86s + 1035) Continuous-time zero/pole/gain model.
When you call d2c without specifying a method, the function uses ZOH by default. The ZOH interpolation method increases the model order for systems that have real negative poles. This order increase occurs because the interpolation algorithm maps real negative poles in the z domain to pairs of complex conjugate poles in the s domain.
Convert G to continuous time using the Tustin method.
Gct = d2c(G,'tustin')
Gct = 0.083333 (s+60) (s-20) ---------------------- (s-60) (s-13.33) Continuous-time zero/pole/gain model.
In this case, there is no order increase.
Compare frequency responses of the interpolated systems with that of G.
In this case, the Tustin method provides a better frequency-domain match between the discrete system and the interpolation. However, the Tustin interpolation method is undefined for systems with poles at z = –1 (integrators), and is ill-conditioned for systems with poles near z = –1.