1. Digital Control Systems Stability Analysis of Discrete Time Systems

2. Mapping Between the s-plane and the z-plane

8. Stability Analysis of Discrete Time Systems BIBO Stability An initially relaxed (all the initial conditions of the system are zero) LTI system is said to be BIBO stable if for every bounded input, the output is also bounded. However, the stability of the following closed loop system can be determined from the location of closed loop poles in z-plane which are the roots of the characteristic equation

9. Stability Analysis of Discrete Time Systems BIBO Stability 1.For the system to be stable, the closed loop poles or the roots of the characteristic equation must lie within the unit circle in z-plane. Otherwise the system would be unstable. 2.If a simple pole lies at |z| = 1, the system becomes marginally stable. Similarly if a pair of complex conjugate poles lie on the |z| = 1 circle, the system is marginally stable. Multiple poles on unit circle make the system unstable.

10. Stability Analysis of Discrete Time Systems BIBO Stability Example: Determine the closed loop stability of the system shown in Figure when K = 1.

11. Stability Analysis of Discrete Time Systems BIBO Stability Example:

12. Stability Analysis of Discrete Time Systems BIBO Stability Stability Tests Applied to characteristic equation Schur-Cohn stability test Jury Stability test Routh stability coupled with bi-linear transformation. Applied to state space Lyapunov stability analysis

13. Stability Analysis of Discrete Time Systems Jury Stability Test Jury Table

14. Stability Analysis of Discrete Time Systems Jury Stability Test Jury Table

15. Stability Analysis of Discrete Time Systems Jury Stability Test Jury Table The system will be stable if:

16. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

17. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

18. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

19. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

20. Stability Analysis of Discrete Time Systems Jury Stability Test Singular Cases

21. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

22. Stability Analysis of Discrete Time Systems Jury Stability Test Example:

23. Stability Analysis of Discrete Time Systems Bilinear Transformation The bilinear transformation has the following form. where a, b, c, d are real constants.If we consider a = b = c = 1 and d = −1, then thetransformation takes a form This transformation maps the inside of the unit circle in the z-plane into the left half of the w-plane

24. Stability Analysis of Discrete Time Systems Bilinear Transformation Let the inside of the unit circle in z-plane can be represented by:

25. Stability Analysis of Discrete Time Systems Bilinear Transformation Let the inside of the unit circle in z-plane can be represented by:

26. Stability Analysis of Discrete Time Systems Routh Stability Criterion

27. Stability Analysis of Discrete Time Systems Routh Stability Criterion Necessary and sufficient condition for all roots of Q(w) to be located in the left-half plane is that all the are positive and all of the coefficients in the first column be positive.

28. Stability Analysis of Discrete Time Systems Routh Stability Criterion Example: There is one sign change in the first column of the Routh array. Thus the system is unstable with one pole at right hand side of the w-plane or outside the unit circle of z-plane.

29. Stability Analysis of Discrete Time Systems Routh Stability Criterion Example: All elements in the first column of Routh array are positive. Thus the system is stable.

30. Stability Analysis of Discrete Time Systems Routh Stability Criterion Example: Find out the range of K for which the system is stable.

31. Stability Analysis of Discrete Time Systems Routh Stability Criterion Example:

32. Stability Analysis of Discrete Time Systems Routh Stability Criterion Example:

33. Stability Analysis of Discrete Time Systems Routh Stability Criterion Singular cases The first element in any row is zero→replace zero by a small number and then proceed with the tabulation. All the elements in a single row are zero o Pairs of real roots with opposite signs. o Pairs of imaginary roots. o Pairs of complex conjugate roots which are equidistant from the origin. → an auxiliary equation is formed by using the coefficients of the row just above the row of all zeros. The tabulation is continued by replacing the row of zeros by the coefficients of