Speed control with PID in Simulink - Mini Project: Build & Apply

Speed control with PID

📖 Scenario: You are working on a simple speed control system for a motor. The motor speed needs to be controlled to reach a target speed smoothly and accurately. You will use a PID controller concept to adjust the motor speed based on the error between the target speed and the current speed.

🎯 Goal: Build a simple Python program that simulates a motor speed control using a PID controller. You will create the data for speeds, set PID parameters, apply the PID control logic, and output the adjusted motor speeds.

📋 What You'll Learn

Create a dictionary with current motor speeds for three motors

Create a variable for the target speed

Write a loop that calculates the PID control output for each motor

Print the adjusted speeds after applying the PID control

💡 Why This Matters

🌍 Real World

PID controllers are widely used in real machines like motors, robots, and vehicles to keep speeds or positions steady and accurate.

💼 Career

Understanding PID control logic is important for roles in automation, robotics, and control systems engineering.

1

Create current motor speeds dictionary

Create a dictionary called current_speeds with these exact entries: 'motor1': 45, 'motor2': 50, 'motor3': 55 representing the current speeds of three motors.

Simulink

# Create the current_speeds dictionary with motor speeds
# Your code here

Hint

Use curly braces to create a dictionary with keys as motor names and values as speeds.

2

Set the target speed

Create a variable called target_speed and set it to 60 representing the desired speed for all motors.

Simulink

current_speeds = {'motor1': 45, 'motor2': 50, 'motor3': 55}
# Set the target_speed variable to 60
# Your code here

Hint

Just assign the number 60 to the variable named target_speed.

3

Calculate PID control output for each motor

Create an empty dictionary called adjusted_speeds. Use a for loop with variables motor and speed to iterate over current_speeds.items(). For each motor, calculate the error as target_speed - speed. Then calculate the adjusted speed as speed + 0.1 * error (this simulates a simple proportional control). Store the adjusted speed in adjusted_speeds with the motor as the key.

Simulink

current_speeds = {'motor1': 45, 'motor2': 50, 'motor3': 55}
target_speed = 60
# Calculate adjusted speeds using a for loop and proportional control
# Your code here

Hint

Use a for loop to go through each motor and calculate the new speed using the error and a proportional factor of 0.1.

4

Print the adjusted speeds

Write a print statement to display the adjusted_speeds dictionary.

Simulink

current_speeds = {'motor1': 45, 'motor2': 50, 'motor3': 55}
target_speed = 60
adjusted_speeds = {}
for motor, speed in current_speeds.items():
    error = target_speed - speed
    adjusted_speed = speed + 0.1 * error
    adjusted_speeds[motor] = adjusted_speed
# Print the adjusted_speeds dictionary
# Your code here

Hint

Use print(adjusted_speeds) to show the final adjusted speeds.

Practice

1. What is the main purpose of using a PID controller in speed control systems in Simulink?

easy

A. To randomly change the speed for testing

B. To increase the machine speed without limits

C. To stop the machine immediately

D. To keep the machine speed steady and close to the target

Solution

1. Step 1: Understand the role of PID controller

   A PID controller adjusts the speed by balancing three parts: proportional, integral, and derivative to maintain steady speed.

2. Step 2: Identify the main goal in speed control

   The goal is to keep the speed steady and close to the desired target, avoiding sudden changes or overshoot.

3. Final Answer:

   To keep the machine speed steady and close to the target -> Option D

4. Quick Check:

   PID controls speed stability = To keep speed steady [OK]

Hint: PID keeps speed steady near target by adjusting smoothly [OK]

Common Mistakes:

• Thinking PID increases speed without limit
• Believing PID causes random speed changes
• Assuming PID stops the machine immediately

2. Which of the following is the correct way to add a PID Controller block in Simulink for speed control?

easy

A. Drag the PID Controller block from the Simulink Library Browser and connect it to the motor model

B. Write pid() function in the MATLAB command window only

C. Use the 'Gain' block instead of PID Controller block

D. Add a 'Scope' block and rename it to PID Controller

Solution

1. Step 1: Identify how to add PID in Simulink

   Simulink uses blocks from its Library Browser; the PID Controller block is dragged and connected to the system.

2. Step 2: Check other options for correctness

   Writing pid() in MATLAB does not add a block in Simulink; 'Gain' block is not a PID; renaming 'Scope' does not create PID functionality.

3. Final Answer:

   Drag the PID Controller block from the Simulink Library Browser and connect it to the motor model -> Option A

4. Quick Check:

   PID block added by drag-drop in Simulink [OK]

Hint: Add PID block by dragging from Simulink Library [OK]

Common Mistakes:

• Trying to write PID code in MATLAB instead of using block
• Using Gain block as PID controller
• Renaming unrelated blocks to PID

3. Given this Simulink PID speed control setup, what will be the output speed if the setpoint is 1000 RPM and the PID gains are tuned correctly?

Setpoint = 1000 RPM
Initial speed = 0 RPM
PID gains: P=1, I=0.5, D=0.1
Simulation time = 10 seconds

medium

A. Speed will reach and stay close to 1000 RPM

B. Speed will stay at 0 RPM

C. Speed will overshoot to 2000 RPM and stay there

D. Speed will oscillate wildly without settling

Solution

1. Step 1: Understand PID tuning effect

   Properly tuned PID gains help the speed reach the setpoint smoothly without large overshoot or oscillations.

2. Step 2: Predict output behavior

   Starting from 0 RPM, the PID will increase speed to near 1000 RPM and maintain it steadily within simulation time.

3. Final Answer:

   Speed will reach and stay close to 1000 RPM -> Option A

4. Quick Check:

   Correct PID tuning = steady speed near setpoint [OK]

Hint: Good PID tuning means speed reaches setpoint smoothly [OK]

Common Mistakes:

• Assuming speed stays at zero without control
• Expecting large overshoot without reason
• Thinking speed oscillates wildly if tuned well

4. You built a PID speed control model in Simulink but the motor speed never reaches the setpoint and stays low. What is the most likely error?

medium

A. The Scope block is not connected

B. The motor block is missing from the model

C. PID gains are too low, causing weak control action

D. The setpoint value is set to zero

Solution

1. Step 1: Analyze symptoms of low speed

   If speed stays low and does not reach setpoint, weak control action is likely due to low PID gains.

2. Step 2: Check other options for feasibility

   Missing motor block would cause no output; zero setpoint means target is zero; Scope block only displays signals and does not affect control.

3. Final Answer:

   PID gains are too low, causing weak control action -> Option C

4. Quick Check:

   Low PID gains = weak control, speed stays low [OK]

Hint: Low PID gains cause weak control and low speed [OK]

Common Mistakes:

• Ignoring PID gain tuning importance
• Confusing Scope block role with control
• Assuming setpoint zero when it is not

5. You want to improve the speed control of a motor in Simulink using a PID controller. The motor speed shows oscillations around the setpoint. Which combination of PID tuning changes will most likely reduce oscillations?

hard

A. Increase the integral gain and decrease the derivative gain

B. Decrease the proportional gain and increase the derivative gain

C. Increase the proportional gain and integral gain equally

D. Remove the derivative gain completely

Solution

1. Step 1: Understand oscillations cause

   Oscillations often happen when proportional gain is too high, causing overreaction to error.

2. Step 2: Effect of derivative gain

   Increasing derivative gain helps dampen oscillations by reacting to speed change rate.

3. Step 3: Choose tuning changes to reduce oscillations

   Decreasing proportional gain reduces aggressive response; increasing derivative gain adds damping, together reducing oscillations.

4. Final Answer:

   Decrease the proportional gain and increase the derivative gain -> Option B

5. Quick Check:

   Lower P and higher D reduce oscillations [OK]

Hint: Lower P gain and raise D gain to reduce oscillations [OK]

Common Mistakes:

• Increasing integral gain which can worsen oscillations
• Removing derivative gain which dampens oscillations
• Increasing proportional gain causing more oscillations