mpc: utils: model.py - allows for design of neural network and loss function

    processdata.py - helper function for constructing datasets

    diamond_I_configuration_v5.py - helper function for initialising DLS actuators and sensors

    sim_mpc.py - implements simulation with various controllers


simulation_mpc.py - Executable, runs full simulation with MPC solving with OSQP or FGM as specified


test_model.py - Executable:
                Runs partial simulation with first n states of system 
                Runs comparison between nn and mpc
                Uses DAGGER for generating datasets
                Generates datasets from various disturbances 

train.py - Executable, trains network with data saved from test_model.py

evaluateModels.py - Executable, evaluates model performance over various trajectories

lqr.py - Executable, generate LQR training data based on random sampling

datatoexpert.py - Executable, converts u_train.pt etc to expert data file