Manual PID tuning in Simulink - Step-by-Step Execution

Concept Flow - Manual PID tuning

Start with initial PID values

↓

Apply PID to system

↓

Observe system response

↓

Adjust P, I, or D values

↓

Check if response is satisfactory?

No→Repeat adjustment

Yes↓

Finish tuning

Manual PID tuning involves setting initial values, testing system response, adjusting parameters, and repeating until the desired control is achieved.

Execution Sample

Simulink

P = 1.0
I = 0.5
D = 0.1
// Apply PID to system
// Observe response
// Adjust P, I, D
// Repeat until good

This code shows the steps of setting PID values, applying them, observing response, and adjusting parameters manually.

Execution Table

Step	P	I	D	System Response	Action
1	1.0	0.5	0.1	Oscillations present	Increase D to reduce oscillations
2	1.0	0.5	0.2	Oscillations reduced	Increase P to improve speed
3	1.2	0.5	0.2	Faster response, some overshoot	Decrease I to reduce overshoot
4	1.2	0.3	0.2	Good response, minimal overshoot	Check if satisfactory
5	1.2	0.3	0.2	Satisfactory	Finish tuning

💡 Tuning stops when system response is satisfactory with minimal overshoot and oscillations.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
P	1.0	1.0	1.0	1.2	1.2	1.2
I	0.5	0.5	0.5	0.3	0.3	0.3
D	0.1	0.2	0.2	0.2	0.2	0.2
System Response	N/A	Oscillations present	Oscillations reduced	Faster response, some overshoot	Good response, minimal overshoot	Satisfactory

Key Moments - 2 Insights

Why do we increase D when oscillations are present?

Increasing D adds damping to the system, which helps reduce oscillations as shown in step 1 to 2 in the execution_table.

Why decrease I when there is overshoot?

High I can cause overshoot by accumulating error too fast; reducing I at step 3 to 4 reduces overshoot as seen in the system response.

Visual Quiz - 3 Questions

Look at the execution_table at step 3, what is the value of P?

A 1.0

B 0.5

C 1.2

D 0.3

💡 Hint

Check the P column in the execution_table row for step 3.

At which step does the system response become satisfactory?

A Step 5

B Step 2

C Step 4

D Step 3

💡 Hint

Look at the System Response and Action columns in the execution_table.

If we increase I instead of decreasing it at step 3, what would likely happen?

A Oscillations would reduce

B Overshoot would increase

C Response speed would decrease

D System would become stable immediately

💡 Hint

Refer to the key_moments explanation about I and overshoot.

Concept Snapshot

Manual PID tuning steps:
1. Set initial P, I, D values
2. Apply PID to system
3. Observe system response
4. Adjust P, I, D based on response
5. Repeat until response is satisfactory
Key: Increase D to reduce oscillations, decrease I to reduce overshoot.

Full Transcript

Manual PID tuning is a process where you start with initial values for the proportional (P), integral (I), and derivative (D) gains. You apply these to your system and watch how it responds. If the system oscillates, you increase D to add damping. If the system is slow, you increase P to speed it up. If there is overshoot, you reduce I to prevent error accumulation from causing too much correction. You repeat these steps, adjusting the values and observing the response until the system behaves well with minimal overshoot and oscillations. This step-by-step approach helps you find the right balance for your PID controller.

Practice

1. What is the main goal of manual PID tuning in Simulink?

easy

A. Replacing the PID controller with a different control method

B. Automatically calculating PID parameters using software

C. Adjusting Kp, Ki, and Kd values by hand to improve system response

D. Running the simulation without changing any parameters

Solution

1. Step 1: Understand manual PID tuning

   Manual PID tuning means changing the PID gains (Kp, Ki, Kd) by hand, not automatically.

2. Step 2: Identify the goal of tuning

   The goal is to improve system response by adjusting these values and testing repeatedly.

3. Final Answer:

   Adjusting Kp, Ki, and Kd values by hand to improve system response -> Option C

4. Quick Check:

   Manual tuning = Adjust PID gains by hand [OK]

Hint: Manual tuning means changing PID values yourself [OK]

Common Mistakes:

• Thinking tuning is automatic
• Confusing tuning with replacing controller
• Ignoring the role of Kp, Ki, Kd

2. Which of the following is the correct way to increase the proportional gain in a Simulink PID block manually?

easy

A. Set the Kp parameter to a higher value in the PID block dialog

B. Increase the Ki parameter to speed up response

C. Decrease the Kd parameter to reduce overshoot

D. Change the sample time to a smaller value

Solution

1. Step 1: Identify the proportional gain parameter

   Kp is the proportional gain parameter in the PID block.

2. Step 2: Understand how to increase Kp

   Increasing Kp means setting its value higher in the PID block dialog box.

3. Final Answer:

   Set the Kp parameter to a higher value in the PID block dialog -> Option A

4. Quick Check:

   Increase Kp by raising its value [OK]

Hint: Increase Kp by raising its value in PID block [OK]

Common Mistakes:

• Confusing Kp with Ki or Kd
• Changing sample time instead of gains
• Decreasing Kd to increase Kp

3. Given a system with initial PID gains Kp=1, Ki=0.5, Kd=0.1, after manual tuning you set Kp=3, Ki=0.5, Kd=0.1. What is the expected effect on the system response?

medium

A. Slower response with less overshoot

B. Faster response with possible increased overshoot

C. No change in response

D. System becomes unstable immediately

Solution

1. Step 1: Analyze effect of increasing Kp

   Increasing Kp from 1 to 3 increases proportional action, speeding response but may cause overshoot.

2. Step 2: Ki and Kd unchanged

   Ki and Kd remain same, so integral and derivative effects stay constant.

3. Final Answer:

   Faster response with possible increased overshoot -> Option B

4. Quick Check:

   Higher Kp = faster but more overshoot [OK]

Hint: Higher Kp speeds response but may overshoot [OK]

Common Mistakes:

• Assuming Ki or Kd changes
• Thinking response slows down with higher Kp
• Believing system instantly unstable

4. You manually set Kp=0, Ki=0, Kd=0 in a Simulink PID block and run the simulation. What is the most likely problem?

medium

A. The system will respond perfectly with no error

B. The system will oscillate wildly

C. The simulation will produce an error and stop

D. The system will not respond to input changes

Solution

1. Step 1: Understand zero gains effect

   Setting Kp, Ki, Kd all to zero means no control action is applied.

2. Step 2: Predict system behavior

   Without control, system output won't change in response to input or error.

3. Final Answer:

   The system will not respond to input changes -> Option D

4. Quick Check:

   Zero gains = no control response [OK]

Hint: Zero all gains means no control action [OK]

Common Mistakes:

• Expecting oscillations with zero gains
• Thinking simulation errors occur
• Assuming perfect response with zero gains

5. You want to reduce steady-state error in your Simulink model using manual PID tuning. Which parameter should you increase and why?

hard

A. Increase Ki to eliminate steady-state error by adding integral action

B. Increase Kp to reduce overshoot and steady-state error

C. Increase Kd to speed up response and reduce steady-state error

D. Decrease Ki to avoid steady-state error

Solution

1. Step 1: Identify parameter affecting steady-state error

   Integral gain Ki helps eliminate steady-state error by accumulating error over time.

2. Step 2: Understand effect of increasing Ki

   Increasing Ki adds integral action, which corrects persistent error and reduces steady-state offset.

3. Final Answer:

   Increase Ki to eliminate steady-state error by adding integral action -> Option A

4. Quick Check:

   Ki controls steady-state error elimination [OK]

Hint: Increase Ki to fix steady-state error [OK]

Common Mistakes:

• Confusing Kp or Kd effect on steady-state error
• Decreasing Ki instead of increasing
• Ignoring integral action role