A PID controller is used to control the state of a process. The controller uses proportional, integral and derivative gains to provide control signals to the system. PID automatically applies an accurate and responsive correction to a control function. The control function in our case is the function to change the temperature. A PID controller continuously calculates an error value e(t) as the difference between a desired setpoint and a measured process variable (current temperature in our case) and applies a corrective measure based on proportional, integral and derivative terms (denoted P, I and D respectively).

LSTM stands for Long Short-Term Memory networks which are used in the field of Deep Learning. LSTM has feedback connections, i.e., it is capable of processing the entire sequence of data, apart from single data points such as images. This finds application in speech recognition, machine translation, etc. LSTM processes an input, gives an output and then uses the output of the prior step along with the current input to give the current output. The LSTM model also receives a 'state' information along with the input of the current state and the output of the prior step. The state contains different gates (input, output, forget) to store the relevant information. LSTM is a special kind of RNN (Recurrent Neural Network), which shows outstanding performance on a large variety of problems.