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\nLSTM Replaces PID Control\n

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\nThe purpose of this exercise is to automate a temperature control process with an LSTM network. The LSTM network is trained from a PID (Proportional Integral Derivative) controller or a Model Predictive Controller (MPC). LSTM (Long Short...\nThe purpose of this exercise is to automate a temperature control process with an LSTM network. The LSTM network is trained from a PID (Proportional Integral Derivative) controller or a Model Predictive Controller (MPC). LSTM (Long Short Term Memory) networks are a special type of RNN (Recurrent Neural Network) that is structured to remember and predict based on long-term dependencies that are trained with time-series data. An LSTM repeating module has four interacting components.

The LSTM is trained (parameters adjusted) with an input window of prior data and minimized difference between the predicted and next measured value. Sequential methods predict just one next value based on the window of prior data. In this case, the error between the set point and measured value is the feature and the heater value is the output label. Proportional Integral Derivative (PID) control automatically adjusts a control output based on the difference between a set point (SP) and a measured process variable (PV).

Objective: Train and deploy an LSTM network to adjust the heater (Q) to regulate the TCLab temperature to a requested set point.\n
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Resource Details

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Media Length
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29:52
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Grade
10th - Higher Ed
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Subjects
STEM
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Source:
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\nAPMonitor.com\n\n
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Date
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2022
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Language
English
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For Teacher Use
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Fine Print: Educational Use
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apmonitor, lstm, pid, proportional, integral, derivative, lstm control, machine learning, good job, separate program, tc lab, set point, pid controller, pickle file, csv file, h5 file, lstm network, case study, loss function, validation loss, arduino device, test set, model file, lstm model, heater output, controller, control, file, loss, validation, model, case, 15 values, heater
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