Advantages and Disadvantages When Using Derivative

Advantages and disadvantages when using derivative Advantages The derivative control mode gives a controller additional control action when the error chan ges consistently. It also makes the loop more stable (up to a point) which allows using a higher  hi gher  controller gain and a faster integral (shorter integral time or higher integral gain). These have the effect of reducing the maximum deviation of process variable from set point if  the process receives and external disturbance. For a typical temperature control loop, you can expect a 20% reduction in the maximum deviation. Figure 2 shows how a loop with derivative (PID) control recovers quicker from a disturbance with less deviation than a loop with P or PI PI control

Figure 2 

Derivative action is used to make the control faster 

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When the controller has derivative action only, its output change is proportional to the rate of change of the deviation

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If the rate of change of the deviation is slow, output changes only slightly from the value where the deviation is fast, output change will be more.

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Constant deviation does not cause any an y action of the controller output

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A ‘step change’ in deviation will cause the output to go to an infinitely high or low value

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Proportional and derivative actions are always used together 

Disadvantages Noisy PV

Using the derivative control mode is a bad idea when the process variable (PV) has a lot of noise on it. ‘Noise’ is small, random, rapid changes in t he PV, and consequently rapid changes in the error. Because the derivative mode extrapolates the current slope of the error, it is highly affected  by noise (Figure 3). You could try to filter the PV so you can use derivative, as long as your filter  time constant is shorter than 1/5 of your derivative time.

Figure 3. Effect of Noise on Derivative. Process Dynamics

On dead-time dominant processes, PID control do es not always work better than PI control (it depends on which tuning method you use). If the time constant (tau) is equal to or longer than the dead time (td), like in Figure 4, PID control easily outperforms PI control.

Figure 4. Process Dynamics. Temperature and Level Loops

Temperature control loops normally have smooth measurements and lon g time constants. The  process variable of a temperature loop tends to move in the same direction for a long time, so its

slope can be used for predicting future error. So temperature loops are ideal candidates for using derivative control – if needed. Level measurements can be very noisy on boiling liquids or gas separation processes. However, if the level measurement is smooth, level c ontrol loops also lend themselves very well to using derivative control (except for surge tanks and averaging level control where you don’t need the speed). Flow Control Loops

Flow control loops tend to have noisy PVs (depending on the flow measurement technology used). They also tend to have short time constants. And they normally act quite fast already, so speed is not an issue. These factors all make flow control loops po or candidates for using derivative control. Pressure Control Loops

Pressure control loops come in two flavors: liquid and g as. Liquid pressure behaves very much like flow loops, so derivative should not be used. Gas pressure loops behave more like temperature loops (some even behave like level loops / integrating processes), making them good candidates for using derivative control. Final Words

Derivative control adds another dimension of complex ity to control loops. It does have its  benefits, but only in special cases. If a loop does not absolutely need derivative control, don’t  bother with it. However, if you have a lag-dominant loop with a smooth process variable that needs every bit of speed it can get, go for the derivative.