Machine learning models +
PLC Control Systems and
Can a PLC run FuzzyLogic by itself?
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Today, most traditional PLCs do not run machine learning models directly, but several modern PLC platforms either support AI features themselves or integrate with AI software running on edge computers or the cloud.
Friendly Introduction to Machine Learning
https://www.youtube.com/watch?v=IpGxLWOIZy4
Can a PLC run machine learning by itself?
Can a PLC run machine learning by itself?
Usually no. The common architecture is:
PLC collects sensor data.
An industrial PC or edge computer runs the machine learning model.
The AI sends results back to the PLC.
The PLC makes real-time control decisions.
This approach is more practical because machine learning models generally require more computing power than a PLC provides.
If you're starting a new AI + PLC project
If you're starting a new AI + PLC project
A good combination is:
PLC: SIMATIC S7-1500 or TwinCAT 3
Machine Learning: Python with TensorFlow, PyTorch, or ONNX running on an industrial PC
Communication: OPC UA, MQTT, or Ethernet/IP
Since you've previously worked with PLCs and industrial automation, learning how to connect PLCs with Python-based AI on an edge computer is likely to be more valuable than looking for a PLC that performs machine learning entirely on its own.
Can a PLC run FuzzyLogic by itself?
Can a PLC run FuzzyLogic by itself?
Yes. Unlike machine learning, fuzzy logic can run directly on many PLCs, provided the PLC has enough memory and processing power.
Many PLCs support fuzzy logic through built-in function blocks, add-on libraries, or custom programming.
Examples include:
Siemens SIMATIC S7-1500 – Can implement fuzzy logic using function blocks or user-created algorithms.
Mitsubishi Electric MELSEC iQ-R – Supports fuzzy control through programming.
Omron NJ Series – Suitable for fuzzy control applications.
Schneider Electric Modicon M580 – Can execute fuzzy logic algorithms in PLC code.
Typical applications of fuzzy logic in PLCs
Typical applications of fuzzy logic in PLCs
Temperature control
Motor speed control
HVAC systems
Water level control
Conveyor speed optimization
Robotic motion control
For industrial control, fuzzy logic remains a practical choice because it is lightweight, predictable, and compatible with PLC scan cycles. Machine learning is more commonly used alongside the PLC rather than inside it.
Fuzzy Logic Control on Gas Turbine Generator with Allen Bradley PLC
https://www.youtube.com/watch?v=IVr17ow7wxM
SIEMENS FUZZY CONTROL++ | Temperature control part1 | STEP 7 | S7-300 | S7-400
https://www.youtube.com/watch?v=HLi8LiVzAys
SIEMENS FUZZY CONTROL++ for aggressive temperature control (part 2) | STEP 7 | S7-300 | S7-400
https://www.youtube.com/watch?v=9tMjaMlDnVs
SIEMENS FUZZY CONTROL++ for conservative temperature control (part 3) | STEP 7 | S7-300 | S7-400
https://www.youtube.com/watch?v=MjbtyAs9-t4
Automatic Mixing Color System (Fuzzy Logic with PLC S7-1200 Siemens )
https://www.youtube.com/watch?v=t2-gLIk6gtw
Fuzzy logic algorithm
https://www.youtube.com/watch?v=jySVkivpBWU
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