This data repository supports the ETFA24 publication titled "Scheduled Sampling Training Framework for ANN-Based PID Control," part of the E-TROTLE project. This project is funded under MCIN/AEI/10.13039 /501100011033 project TED2021-129134B-I00 co-funded with the European Union ‘‘NextGenerationEU’’/PRTR funds. ETROTLE aims to develop data-driven control systems using transfer learning and optimization methods to enhance the operation of wastewater treatment plants (WWTPs), focusing on environmental impact and sustainability. To run the ETFA24 simulations, please combine the data in this repository with the code available in the associated "ETFA24_SS" GitHub repository in https://github.com/ilChapo/ETFA24_SS

METHODOLOGICAL INFORMATION

1. Description of methods used for collection-generation of data: SIMULINK simulation jointly with our tuning functions allowed for selection of the PID parameters and obtention of the simulation vectors.

2. Instrument- or software- specific information needed to interpret the data: We used MATLAB_2023a for the simulations and the usort2 tuning rules for the PID.

ETROTLE_Dataset_ETFA24_model_weights: Contains sample model weights in .h5 format for one iteration of the SS (Scheduled Sampling) and NS (Non-Scheduled) training simulations across all first-order processes. ETROTLE_Dataset_ETFA24_Scalers: Includes the scalers for the ANN data inputs and outputs used in training for all first-order processes. The scaling values are based on historical data, located in ETROTLE_Dataset_MAT_files under the 1st_order directory. ETROTLE_Dataset_MAT_files: Houses the .mat files of historical data for first-order processes, including the control actuations of all reference PIDs and the process outputs ("mesura") for each process. Inside we find the reference folder: Contains the variable setpoint signals used in all simulations. PID_tuning_params_1stO_processes.mat: Provides the tuned parameters for all PIDs, jointly with the dynamics of 10 different first-order processes.