# Control Systems Engineering ( Chapter 6. Stability ) Prof. Kwang-Chun Ho Tel: Fax:

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1 Control Systems Engineering ( Chapter 6. Stability ) Prof. Kwang-Chun Ho Tel: Fax:

2 Introduction In this lesson, you will learn the following : How to determine the stability of a system represented as a transfer function How to determine the stability of a system represented in state-space How to determine system parameters to yield stability 2

3 Introduction What is stability? Most important system specification We cannot use a control system if the system is unstable Stability is subjective There are many definitions for stability, depending on the kind of system or the point of view We limit ourselves to linear time invariant (LTI) systems The total response of a system is the sum of the forced and natural response, ct c t c t forced natural 3

4 Introduction Using these concepts, we present the following definitions of stability, instability and marginal stability A linear time invariant system is stable if the natural response approaches to zero as time approaches to infinity A linear time invariant system is unstable if the natural response grows without bound as time approaches to infinity A linear time invariant system is marginally stable if the natural response neither decays nor grows but remains constant or oscillates as time approaches to infinity An alternative and best-known definition of stability is as follows : A system is stable if every bounded input yields a bounded output We call this statement the bounded-input, bounded-output (BIBO) definition of stability 4

5 Introduction How do we determine if a system is stable? If the closed loop system poles are in the left-half of the s-plane and hence have a negative real part, the system is stable Unstable systems have closed loop system transfer functions with at least one pole at the right half plane and/or poles of multiplicity greater than one on the imaginary axis Similarly, marginally stable systems have closed loop transfer function with only imaginary axis poles of multiplicity 1 and poles in the left half plane As an example, the unit step responses of a stable and an unstable system are shown in figure (a) and (b) 5

6 Introduction Marginally stable 6

7 In this section, we will learn a method that yields stability information without the need to solve for closed loop system poles The method is called the Routh-Hurwitz criterion for stability (Routh, 1905) The method requires two steps : Generate a data table called a Routh table Interpret the Routh table to tell how many closed loop system poles are in the left half plane, the right half plane, and on the imaginary axis Generating a Basic Routh Table: Look at the equivalent closed-loop transfer function shown in figure 7

8 Since we are interested in the system poles, we focus our attention on the denominator We first create the Routh table shown in Table Begin by labelling the rows with powers of s from the highest power of the denominator of the closed loop transfer function to s 0 8

9 Next, start with the coefficient of the highest power of s in the denominator and list, horizontally in the first row, every other coefficient In the second row, list horizontally, starting with the highest power of s, every coefficient that was skipped in the first row The remaining entries are filled in as follows: Each entry is a negative determinant of entries in the previous two rows divided by the entry in the first column directly above the calculated row The left-hand column of the determinant is always the first column of the previous two rows, and the right-hand column is the elements of the column above and to the right The table is complete when all of the rows are completed down to s 0 Table 6.2 is the completed Routh table 9

10 Example: Make the Routh table for the system shown in the figure 10

11 Solution: The first step is to find the equivalent closed loop system because we want to test the denominator of this function, not the given forward transfer function, for pole location Using the feedback formula, we obtain the equivalent system of figure(b) The Routh-Hurwitz criterion will be applied to this denominator 11

12 First, label the rows with powers of s from s 3 down to s 0 in a vertical column Next, form the first row of the table, using the coefficients of the denominator Start with the coefficient of the highest power and skip every other power of s Now form the second row with the coefficients of the denominator skipped in the previous step Subsequent rows are formed with determinants as shown in table For convenience, any row of the Routh table can be multiplied by a positive constant without changing the values of rows below For example, in the second row of table, the row was multiplied by 1/10 Interpreting the Basic Routh Table : Now that we know how to generate the Routh table, let us see how to interpret it 12

13 Simply stated, the Routh-Hurwitz criterion declares that the number of roots of the polynomial that are in the right half plane is equal to the number of sign changes in the first column If the closed loop transfer function has all poles in the left half of the s-plane, the system is stable Thus, a system is stable if there are no sign changes in the first column of the Routh table For example, the following table has two sign changes in the first column The first sign changes occurs from 1 in the s 2 row to -72 in the s 1 row The second occurs from -72 in the s 1 row to 103 in the s 0 row Thus, the system is unstable since two poles exist in the right half plane 13

14 Example: Make a Routh table and tell how many roots of the following polynomial are in the right half-plane and in the left half-plane Solution: P s 3s 9s 6s 4s 7s 8s 2s 6 14

15 : Special Cases Two special cases can occur: The Routh table sometimes will have a zero only in the first column of a row The Routh table sometimes will have an entire row that consists of zeros Example: Determine the stability of the closed loop transfer function Solution: Begin by assembling the Routh table down to the row where a zero appears only in the first column (the s 3 row) Next replace the zero by a very small number,, and complete the table 10 T ( s) s 2s 3s 6s 5s 3 15

16 (a) (b) To begin the interpretation, we must firs assume a sign, positive or negative, for the quantity, table(b) shows the first column of table(a) along with the resulting signs for choices of positive and negative If is chosen negative table(b) will show a sign change from the s 3 row to the s 2 row, and there will be another sign change from the s 2 row to the s 1 row 16

17 Example: Hence, the system is unstable and has two poles in the right half plane Alternatively, we could choose negative Table(b) would then show a sign change from the s 4 row to the s 3 row Another sign change would occur from the s 3 row to the s 2 row One result would be exactly the same as that for a positive choice for Thus, the system is unstable, with two poles in the right half plane Tell how many roots of the following polynomial are in the right half-plane, in the left half-plane, and on the -axis: Solution: j Q s s 2s 2s 4s 11s 10 17

18 Example: Entire Row is Zero Tell how many roots of the following polynomial are in the right half-plane, in the left half-plane, and on the j -axis: Q s s s 3s 2s 2 Solution:

19 Example: When a Routh table has entire row of zeros, the poles could be in the right half plane, or the left half plane or on the j -axis Determine the number of right-half-plane poles in the closed transfer function 10 T ( s) s 7s 6s 42s (Have 2 poles on the j -axis and 2 poles in the left-half plane) 8s 56 19

20 Solution: Start by the forming the Routh table for the denominator At the second row, we multiply through by 1/7 for convenience We stop at the third row, since the entire row consists of the zeros, and use the following procedure First, we return to row immediately above the row of zeros and form an auxiliary polynomial, using the entries in that row as coefficients The polynomial will start with the power of s in the label column and continue by skipping every other power of s 20

21 Example: Thus, the even polynomial formed for this example is Next, we differentiate the polynomial with respect to s, and obtain Finally, we use the coefficients of the last equation to replace the row of zeros Again, for convenience, the third row is multiplied by 1/4 after replacing zeros There are no sign changes, so there are no poles on the right half plane. The system is marginally stable! For the transfer function Ps s s 4 2 () 6 8 dp() s s s ds

22 tell how many poles are the right half plane, or the left half plane or on the -axis Solution j At the s 3 row, we obtain a row of zeros 22

23 Moving back one row to s 4, we extract the even polynomial, P(s), as Taking the derivative for x to obtain the coefficients that replace the row of zeros in the s 3 row, we find Finally, continue the table to the s 0 row, using standard procedure How do we now interpret the Routh table? No sign changes exist from the s 4 row down to the s 0 row Thus, there are no right-half plane poles and the P(s) has all four of its poles on the j -axis The remaining roots of polynomial evaluated from the s 8 row down to the s 4 row have two sign changes and two no sign changes Thus, it has two poles in the right-half plane and the left-half plane, respectively 23

24 Unstable!! Example: Stability Design via Routh-Hurwitz Find the range of the gain K, for the system shown below that will cause the system to be stable, unstable and marginally stable. Assume K > 0 24

25 Solution: First find the closed-loop transfer function as K Gs () ss ( 7)( s 11) K T() s Gs ( ) K 1 s 18s 77s K ss ( 7)( s 11) Next form the Routh table 25

26 Since K assumed positive, we see that all elements in the first column are always positive except the s 1 row This entry can be positive, zero, or negative, depending upon the value of K If K <1386, all terms in the first column will be positive, and since there are no sign changes, the system will have three poles at the left-half plane and be stable(0<k<1386) If K =1386, we have an entire row of zeros, which could signify poles Returning the s 2 row and replacing K with 1386, we form the even polynomial Ps 2 ( ) 18s 1386 Differentiating with respect to s, we obtain dp() s ds 36s 0 j 26

27 Replacing the row of zeros with the coefficients of the last equation, we obtain the following Routh table Since there are no sign changes from the even polynomial (s 2 row) down to the bottom of the table, the even polynomial has its two roots on the j -axis of the unit multiplicity Since there are no sign changes above the even polynomial, the remaining root is in the left-half plane Therefore, the system is marginally stable! 27

28 Stability in State Space Up to this point, we have examined stability from the s- plane viewpoint Now we look at stability from the perspective of state space We know that the values of the system poles are equal to the eigenvalues of the system matrix We stated that the eigenvalues of matrix A were solutions of the equation det(i-a) s, which also yielded the poles of the transfer function (discussed in chapter 3!) 28

29 Example: For the system given below, find out how many poles are in the left half plane, in the right half plane, and on the j -axis x x 0 u, y x Solution: (I-A) s First form : s s 3 1 ( si A) 0 s s s s 2 29

30 det(i-a) s Now find the : 3 2 det( si A) s 6s 7s 52 Using this polynomial, form the Routh table Since there is one sign change in the first column, the system has one right half plane pole and two left half plane poles It is therefore unstable 30

31 Homework Assignment #6 (Use Routh table) 31

32 Homework Assignment #6 32

33 Homework Assignment #6 33

34 Homework Assignment #6 34

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