This happens to also be the first term – the Proportional response. This is the error between the process variable PV(t) – the thing you want to control – and the setpoint SP(t) – the value you want the process to be at. The main variable in the equation above is e(t). Which naturally leads to the P, I, and D in the name and the three weighting parameters (gains) that need to be tuned: How much error has accumulated over time.Error between where you want the process to be (a setpoint) and where the process is.In fact, that’s where I got all the information I needed since my control theory text is currently buried in a closet somewhere.Ī PID controller produces an output (aka a “Manipulated Variable”, MV(t) or u(t)) – usually from 0 to 100% – based on a weighted sum of three terms: I studied the theory behind it in college and even built a LabVIEW UI for use in a student teaching lab.įor more detailed information, the obligatory Wikipedia link should be a good starting point. What’s important is that you don’t need to know much about a process to control it with a PID controller. Yes, I know I have a strange idea of fun.īackgroundPID control is a heuristic method of automatically controlling processes as wide ranging as water levels in tanks to the direction of ships running against a current. On a whim, I thought it might be fun to try to implement a PID control algorithm … in R.
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