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I wish I knew what a controller is!
I’ve got a good analogy for a controller in automation. Imagine your entire body as a fully automated process. The controller in this case is your brain. It interprets the data from its field devices (your senses) and decides what actions to take. Let’s break it down a little more.
Imagine you’re at the beach, sun beating down and no shade in sight. You’re hot. So your brain processes that idea and analyze what you can do to cool down. You could strip to your swimsuit and jump in the sea. Or you could order a cold beer, like I do. Either way, your brain processes the data it gets from your skin – temperature above acceptable levels – analyzes your options, and sends signals to your body, telling it what to do.
So for a fully automated process plant, you need three main actions: measure, analyze, and act. The controller does the analyzing bit, just like the brain in our analogy.
To measure your process variables (PV), such as temperature or pressure, you need field devices to monitor your PV and send data to your controller as inputs. If a PV goes out of its desired range, known as the setpoint (SP), the system must act. The controller decides what action needs to happen and sends signals to the final control elements as outputs. The final control elements change the process to make the PV match the SP again.
The market offers many types of controllers to fit certain applications. In a process plant, for example, you’ll likely see a programmable logic controller (PLC) or distributed control system (DCS). In home automation, you can use microcontrollers such as a Raspberry Pie or Arduino. Back in my student days, I used a Motorola HC05, a super-basic microcontroller from the 80s that used the Assembly programming language.
Regardless of complexity, controllers always receive data from sensors or field devices as inputs, analyze this data through a program, and send signals to the actuators as outputs to maintain the process value close to your setpoint.