PID tuning through SCADA in SCADA systems - Step-by-Step Execution

Process Flow - PID tuning through SCADA

Start: Read Process Variable (PV)

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Calculate Error = Setpoint - PV

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Apply PID Formula: P + I + D terms

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Output Control Signal to Actuator

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Process Responds, PV Changes

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SCADA Monitors PV and Output

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Adjust PID Parameters (Kp, Ki, Kd) if needed

↩Back to Calculate Error

The SCADA system continuously reads the process variable, calculates the error, applies the PID formula, sends control signals, monitors responses, and adjusts PID parameters to tune the system.

Execution Sample

SCADA systems

PV = 50
Setpoint = 60
Error = Setpoint - PV
Output = Kp*Error + Ki*Integral(Error) + Kd*Derivative(Error)
Send Output to Actuator
Adjust Kp, Ki, Kd based on response

This code snippet shows the basic PID control loop steps executed through SCADA.

Process Table

Step	Process Variable (PV)	Setpoint	Error	PID Output	Action	Notes
1	50	60	10	Calculate P=Kp*10, I=Ki*0, D=Kd*0	Send output to actuator	Initial error calculation, integral and derivative zero
2	52	60	8	Calculate P=Kp*8, I=Ki*10, D=Kd*(8-10)	Send output to actuator	PV increased, error decreased, integral accumulates
3	55	60	5	Calculate P=Kp*5, I=Ki*18, D=Kd*(5-8)	Send output to actuator	Error smaller, integral grows, derivative negative
4	58	60	2	Calculate P=Kp*2, I=Ki*23, D=Kd*(2-5)	Send output to actuator	Error close to zero, integral high, derivative negative
5	60	60	0	Calculate P=Kp*0, I=Ki*25, D=Kd*(0-2)	Send output to actuator	Error zero, integral max, derivative negative
6	61	60	-1	Calculate P=Kp*(-1), I=Ki*24, D=Kd*(-1-0)	Send output to actuator	PV overshoot, error negative, integral decreases
7	60	60	0	Calculate P=Kp*0, I=Ki*24, D=Kd*(0--1)	Send output to actuator	PV back to setpoint, system stabilizing
Exit	60	60	0	Stable output	No further adjustment	System tuned, error minimized

💡 System reaches setpoint with zero error and stable output, tuning complete

Status Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5	After 6	After 7	Final
PV	50	52	55	58	60	61	60	60	60
Error	10	8	5	2	0	-1	0	0	0
Integral(Error)	0	10	18	23	25	24	24	24	24
Derivative(Error)	0	-2	-3	-3	-2	-1	1	0	0
PID Output	Calc	Calc	Calc	Calc	Calc	Calc	Calc	Calc	Stable

Key Moments - 3 Insights

Why does the integral term keep increasing even when the error is getting smaller?

The integral term sums all past errors, so even if the current error is small, the accumulated sum can still grow, as seen in rows 2 to 5 of the execution_table.

What causes the derivative term to be negative and then positive?

The derivative term measures error change rate. When error decreases quickly, derivative is negative (rows 2-6). When error starts increasing again (overshoot), derivative becomes positive (row 7).

Why does the system output stabilize even when PV slightly overshoots the setpoint?

The PID controller adjusts output based on error and its history, correcting overshoot by reducing output, leading to stabilization as shown in the last steps of the execution_table.

Visual Quiz - 3 Questions

Look at the execution table at step 3. What is the error value?

A 5

B 8

C 2

D 0

💡 Hint

Check the 'Error' column in row 3 of the execution_table.

At which step does the process variable (PV) first reach the setpoint?

A Step 4

B Step 5

C Step 6

D Step 7

💡 Hint

Look at the 'PV' column and find when it equals the 'Setpoint' in the execution_table.

If the integral term was not accumulated, how would the PID output change over steps?

A It would stay constant

B It would only depend on current error and derivative

C It would increase faster

D It would become zero

💡 Hint

Refer to the 'Integral(Error)' column in variable_tracker and its role in PID output.

Concept Snapshot

PID tuning through SCADA:
- Continuously read process variable (PV)
- Calculate error = setpoint - PV
- Compute PID output: P + I + D terms
- Send output to actuator
- Monitor PV and output via SCADA
- Adjust Kp, Ki, Kd to improve control
- Repeat until system stabilizes

Full Transcript

This visual execution shows how a SCADA system performs PID tuning. It starts by reading the process variable and calculating the error from the setpoint. Then it applies the PID formula combining proportional, integral, and derivative terms to compute the control output. This output is sent to the actuator to influence the process. The SCADA system monitors the process variable and output response, adjusting the PID parameters as needed. The execution table traces each step's values, showing how error decreases and the system stabilizes at the setpoint. Key moments clarify common confusions about integral accumulation and derivative sign changes. The quiz tests understanding of error values, setpoint reaching, and the role of integral term in PID output.