自动化专业英语 王树青Unit 1.5Controller Tuning

Unit 1.5 Controller Tuning
1.What are the commonly encountered process control system in a chemical plant ?
2.What must be adjusted after control system in is installed?
3. What method is often used for tuning of a controller?
4. Could you please give the typical approach and steps?
After a control system is installed the controller settings must usually be adjusted until the control system performance is considered to be satisfactory. This activity is referred to as controller tuning or field tuning of the controller. Because controller tuning is usually done by trial and error , it can be quite tedious and time-consuming. Consequently, it is desirable to have good preliminary estimates of satisfactory controller settings. A good first guess may be available from experience with similar control loops. Alternatively, if a process model or frequency response data are available, some special design methods can be employed to calculate controller settings. However, field tuning may still be required to fine rune the controller, especially if the available process information is incomplete or not very accurate General guidelines for selection of controller type (P ,PI.etc. ) and choice of settings are available for commonly encountered process variables: flow rate, liquid level. gas pressure, temperature, and composition. The guidelines discussed below are useful for situations where a process model is not available. However, they should be used with caution because exceptions do occur Similar guidelines are available for selecting the initial controller settings for the startup of a new plant.
Flow Control
Flow and liquid pressure control loops are characterized by fast responses (on the order
of seconds), with essentially no time delays The pfo.ess dynamics are due to compressibility (in a gas stream) or inertial effects (in a liquid). The sensor and signal transmission line may introduce significant dynamic lags if pneumatic instruments are used. Disturbances in flow-control systems tend to be frequent but generally not of large magnitude Most of the disturbances are high-frequency noise (periodic or random) due to stream turbulence, valve changes, and pump vibration. PI flow controllers are generally used with intermediate values of the controller gain Kc. The presence of recurring high-frequency noise rules out the use of derivative action.
Liquid Level
A typical non-self regulating liquid-level process has been discussed, because of its integrating nature. a datively high-gain controller can be used with little concern about instability of the control system. In fact, an increase in controller gain often brings an increase in system stability. while low controller gain can increase the degree of oscillation Integral control action is normally used bur is not necessary if small offsets in the liquid level (±5%) can be tolerated Derivative action is not normally employed in level control, since the level measurements often contain noise due to the ,plashing and turbulence of the liquid entering the tank .
In many level control problems, the liquid storage tank is used as a surge tank to damp out fluctuations in its inlet streams If the exit flow rare from the tank is wed as the manipulated variable , then conservative controller settings should be applied to avoid large ,rapid fluctuation. in the exit flow rate. This strategy is referred to as averaging control if level control also involves heat transfer, such as m a vaporizer or evaporator, the process model and controller design be.ome much more complicated In such situations special control methods can be advantageous.
Gas pressure
Gas pressure is relatively easy to control, except when the gas is in equilibrium with a liquid. A gas pressure process is self-regulating: the vessel (or pipeline) admits more feed
With a the pressure is too low and reduces the make when the pressure becomes too high. PI controllers are normally used with only a small amount of integral control action (i e . ti large) usually the vessel volume is not large, leading to relatively small residence times and time constants .Derivative action is normally not needed because the process response times are usually quite small compared to other process operations.
Temperature
General guidelines for temperature control Loops are difficult to state because of the wide variety of processes and equipment involving heat transfer (and their different time scales). For example, the temperature control problems are quite different for heat exchangers, distillation columns, chemical reactors, and evaporators. Due to the presence of time delays and/or multiple thermal capacitances, there will usually be a stability limit on the controller gain. PID controllers are commonly employed to provide more rapid responses than can be obtained with Pl controllers.
Composition
Composition loops generally have characteristics similar to temperature loops, but with several differences:
1. Measurement noise is a more significant problem in composition loops.
2. Time delays due to analyzers may be a significant factor.
These two factors can limit the effectiveness of derivative action. Due to their importance and the difficulty of control, composition and temperature loops often are prime candidates for the advanced control strategies.
1.5. 2 Trial and error tuning
Controller field tuning is often performed using trial and error procedures suggested by controller manufacturers. A typical approach for PID controllers can he summarized as follows : Step 1. Eliminate integral and derivative action by setting tD at its minimum value and ti at its maximum value
Step 2. Set Kc at a low value (e.g.,0. 5) and put the controller on automatic
Step 3. Increase the controller gain Kc, by small-increments until continuous cycling occurs after a small set-point or load change. The term "continuous cycling" refers to a sustained oscillation with constant amplitude.
Step 4. Reduce Kc by a factor of two
Step 5. Increase ti m small increments until continuous cycling occurs again. Set ti equal to three rimes this value.
Step 6. increase ti until continuous cycling occurs. Set ti equal to one-third of this value.
The value Kc that results in continuous cycling in Step 3 is referred to as the ultimate gain and will be denoted by Kcu. In performing the experimental test, it is important than the controller output does not saturate. If saturation does occur then a sustained oscillation can result even Kc>Kcu
because the concept of an ultimate gain plays such a key role in control system
design and analysis. we present a more formal definition ;
Definition. The ultimate gain Kcu is the largest value of the controller, gain Kcu that results in closed-loop stability when a proportional only controller is used.
If a process model is available ,then Kcu can be calculated theoretically using The stability criteria. The trial and Error tuning procedure described above has a number of disadvantage
1.It is quite time-consuming if a large number of trials is required to optimize Kc, ti, and tD or if
the process dynamics are quit slow. Unit control loop testing may he expensive because of lost productivity or poor product quality.
2.Continuous cycling may be objectionable since the process is pushed to the stability limit.
Consequently, if external disturbances or a change in the process occurs during tuning unstable operation or a hazardous situation could result (e.g. .a "runaway' chemical reactor).
3.This tuning procedure is not applicable to processes that are open-loop unstable because
such processes typically are unstable at both high and low values of Kc, but are stable for an intermediate range f values.
4. Some simple processes do not have an ultimate gain (e. g. , processes that can be accurately modeled一by first-order or second-order transfer functions without time delays)
1.5.3 Continuous cycling method
Trial and error tuning methods based on a sustained oscillation can be considered to be variations of the Famous continuous cycling method that was published by Ziegler and Nichols in 1942. This classic approach is probably the best known method for tuning PID. The continuous cycling approach has also been referred to as loop tuning or the ultimate gain method. The first step is lo experimentally determine Kc. as described in the previous section. The period of the resulting .sustained oscillation is referred to as the ultimate period Pu. The PID controller settings are then calculated from Kc. and Pu using the Ziegler Nichols {Z-N) tuning relations in Table 1.5.1. The Z-N tuning ,elations were empirically developed to provide a l/4 decay ratio. These tuning ,relations have been widely used in industry and serve as a convenient base case for comparing alternative control schemes. However, controller tuning examples presented later in this section indicate that Z-N tuning can be inferior to settings obtained by other methods and should be used with caution~.
Table 1.5.1 Ziegler-Nichols Controller Settings Based on the Continuous Cycling Method
Note chat the Z-N setting for proportional control provides a significant safety
margin since the controller gain is one-half of the stability limit Kcu When integral action is added, Kc is reduced to 0. 45 Kcu or Pl control. However, the addition of derivative action
allows the gain to be increased t0 0. 6Kcu for PID control.
For some control Loops, the degree of oscillation, associated with the l/4 decay ratio and the corresponding large overshoot for set-point changes are undesirable. Thus, more conservative settings are often preferable, such as the modified Z-N settings in Table 1.5.2.
Although widely applied , the Ziegler-Nichols continuous cycling method has some of the same disadvantages as the trial and error method. Howe.er, the continuous cycling method is less time-consuming than the trial and error method because it requires only one trial and error search. Again, we wish to emphasize that the controller settings in Tables 1.5.1 and 1.5.2 should he regarded as first estimates. Subsequent fine tuning via trial and error is often required. especially if the 'original settings" in Table l are selected. Alternatively, the continuous cycling autotuning method discussed at the end of this section may be used.
1.5.4 Process Reaction Curve Method
In their famous paper Ziegler and Nichols proposed a second on-line tuning technique ,the process reaction curve method. This method is based on a single experimental test that is made with the controller in the manual mode . A small step change in the controller output is introduced and the measured process response B(t) is recorded . This step response is also referred to as the process reaction curve. It is characterized by two parameters: S the slope of the tangent through the inflection point ,and θ,the time at which the tangent intersects the time axis.
Two different types of process reaction curves are shown in Figure 1. 5. 1 for step changes occurring at t =0; The response for Case ( a ) is unbounded, which indicates that this process is not self-regulating. in contrast. the hypothetical process considered in Case ( b ) is self-regulating since the process reaction curve reaches a new steady state. Note that the slope-intercept characterization can be used for both types of process reaction curves.
The Ziegler-Nichols tuning relations for the pro.ess reaction curve method are shown in Table1.5 3. S* denotes the normalized slope, S=S/#P where #p is the magnitude of the step change that was introduced in controller output p These Tuning relations were developed empirically to give closed- loop responses with l/4 decay ratios The tuning relations in Table 1.5.3 can be used for both self-regulating and non-self-regulating processes.
If process reaction curve has the typical sigmoidal shape shown in Case (b) of Figure1.5.1, the following model usually provides a satisfactory fit:
whe re B’ is the measured value of the controlled variable and P' is the controller output. both expressed as deviation variables. Note that this model includes the transfer functions the final control element and sensor-transmitter combination, as well as the process transfer function. Model parameters K , t,θand can be determined from the process reaction curve .
The process reaction curve (PRC) method offers several significant advantages,
1. only a single experimental test is necessary.
2. It does not require trial and error.
3. The controller settings are easily calculated.
However. the PRC method also has several disadvantages :
1.The experimental test is performed open-loop conditions. Thus, if a significant load change occurs during the test, no corrective action is taken and the test results may be significantly distorted.
2. it may be difficult to determine the slope at the inflection point accurately, especially if the measurement is noisy and a small recorder chart is used .
3. The method tends to be sensitive to controller calibration errors. By contrast, the Z- N method is less sensitive to calibration errors in Kc since the controller gain is adjusted during the experimental test.
4.The recommended settings in Table1.
5. 2 and Table 1.5.3 tend to result in oscillatory
5 .The method is not recommended for processes that have oscillatory open-loop responses since they were developed to provide a 1/4 decay ratio.
Closed-loop versions of the process reaction curve method have been proposed as a partial remedy for the first disadvantage. fn this approach, a process reaction curve is generated by making a step change in set point during proportional-only control. The model parameters in Eq ( 1.51) are then calculated in a novel manner from the closed-loop response. A minor disadvantage of these closed-loop process reaction methods is that the model parameter calculations aw more complicated than for the standard open-loop method.
Selected From 'Process Dynamics and Control Dale E. Seborg QT Edgar ,John Wiley & Sonsi 1989'
Words and Expressions
1 controller tuning拄控制器整定
2 trail and error 试差法
3 tedious 费时的
4 time-consuming耗时的
5 startup 启动
6 inertial 惯性的
7 vibration 振动
8 turbulence 湍流
9 recur 重复；递归
10. splashing
11.fluctuation 波动起伏
I2. Vaporizer _蒸馏器
13. evaporator 蒸发器，脱水器
14residence time滞留时闸
1 5 ultimate 最终的；临界的
16. loop tuning回路整定
17. decay ratios衰减比
18. be inferior to较…差，在…下面
19. overshoot 超调
20 slope ．斜率；倾斜
21 tangent 切线；正切
22. intersect 相交，交叉
23. hypothetical.假没的，假定的
24. intercept v截止
Z5. sigmoidal S形的
26 chart 图表
27. calibration 刻度，标度；栎准。