Nyquist Stability Criterion

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Presentation transcript:

Nyquist Stability Criterion The Nyquist stability criterion is similar to the Bode criterion in that it determines closed-loop stability from the open-loop frequency response characteristics. The Nyquist stability criterion is based on two concepts from complex variable theory, contour mapping and the Principle of the Argument. Nyquist Stability Criterion. Consider an open-loop transfer function GOL(s) that is proper and has no unstable pole-zero cancellations. Let N be the number of times that the Nyquist plot for GOL(s) encircles the -1 point in the clockwise direction. Also let P denote the number of poles of GOL(s) that lie to the right of the imaginary axis. Then, Z = N + P where Z is the number of roots of the characteristic equation that lie to the right of the imaginary axis (that is, its number of “zeros”). The closed-loop system is stable if and only if Z = 0.

Some important properties of the Nyquist stability criterion are: It provides a necessary and sufficient condition for closed-loop stability based on the open-loop transfer function. The reason the -1 point is so important can be deduced from the characteristic equation, 1 + GOL(s) = 0. This equation can also be written as GOL(s) = -1, which implies that AROL = 1 and , as noted earlier. The -1 point is referred to as the critical point. Most process control problems are open-loop stable. For these situations, P = 0 and thus Z = N. Consequently, the closed-loop system is unstable if the Nyquist plot for GOL(s) encircles the -1 point, one or more times. A negative value of N indicates that the -1 point is encircled in the opposite direction (counter-clockwise). This situation implies that each countercurrent encirclement can stabilize one unstable pole of the open-loop system.

Unlike the Bode stability criterion, the Nyquist stability criterion is applicable to open-loop unstable processes. Unlike the Bode stability criterion, the Nyquist stability criterion can be applied when multiple values of or occur (cf. Fig. 14.3). Example 14.6 Evaluate the stability of the closed-loop system in Fig. 14.1 for: (the time constants and delay have units of minutes) Gv = 2, Gm = 0.25, Gc = Kc Obtain ωc and Kcu from a Bode plot. Let Kc =1.5Kcu and draw the Nyquist plot for the resulting open-loop system.

Solution The Bode plot for GOL and Kc = 1 is shown in Figure 14.7. For ωc = 1.69 rad/min, OL = -180° and AROL = 0.235. For Kc = 1, AROL = ARG and Kcu can be calculated from Eq. 14-10. Thus, Kcu = 1/0.235 = 4.25. Setting Kc = 1.5Kcu gives Kc = 6.38. Figure 14.7 Bode plot for Example 14.6, Kc = 1.

Figure 14.8 Nyquist plot for Example 14.6, Kc = 1.5Kcu = 6.38.

Gain and Phase Margins Let ARc be the value of the open-loop amplitude ratio at the critical frequency . Gain margin GM is defined as: Phase margin PM is defined as The phase margin also provides a measure of relative stability. In particular, it indicates how much additional time delay can be included in the feedback loop before instability will occur. Denote the additional time delay as . For a time delay of , the phase angle is .

Figure 14.9 Gain and phase margins in Bode plot.

or where the factor converts PM from degrees to radians. The specification of phase and gain margins requires a compromise between performance and robustness. In general, large values of GM and PM correspond to sluggish closed-loop responses, while smaller values result in less sluggish, more oscillatory responses. Guideline. In general, a well-tuned controller should have a gain margin between 1.7 and 4.0 and a phase margin between 30° and 45°.

Figure 14.10 Gain and phase margins on a Nyquist plot.

Recognize that these ranges are approximate and that it may not be possible to choose PI or PID controller settings that result in specified GM and PM values. Example 14.7 For the FOPTD model of Example 14.6, calculate the PID controller settings for the two tuning relations in Table 12.6: Ziegler-Nichols Tyreus-Luyben Assume that the two PID controllers are implemented in the parallel form with a derivative filter (α = 0.1). Plot the open-loop Bode diagram and determine the gain and phase margins for each controller.

Figure 14.11 Comparison of GOL Bode plots for Example 14.7.

For the Tyreus-Luyben settings, determine the maximum increase in the time delay that can occur while still maintaining closed-loop stability. Solution From Example 14.6, the ultimate gain is Kcu = 4.25 and the ultimate period is Pu = . Therefore, the PID controllers have the following settings: Controller Settings Kc (min) Ziegler-Nichols 2.55 1.86 0.46 Tyreus-Luyben 1.91 8.27 0.59

The open-loop transfer function is: Figure 14.11 shows the frequency response of GOL for the two controllers. The gain and phase margins can be determined by inspection of the Bode diagram or by using the MATLAB command, margin. Controller GM PM wc (rad/min) Ziegler-Nichols 1.6 40° 1.02 Tyreus-Luyben 1.8 76° 0.79

The Tyreus-Luyben controller settings are more conservative owing to the larger gain and phase margins. The value of is calculated from Eq. (14-14) and the information in the above table: Thus, time delay can increase by as much as 70% and still maintain closed-loop stability.

Figure 14.12 Nyquist plot where the gain and phase margins are misleading.