Design of Distributed Curing Control System for Mass Concrete Pouring The concept of automatic control and intelligent control has emerged in all walks of industry, as has the construction. In order to improve the automation level and reduce the curing cost of poured mass concrete, a distributed control system was designed. A serpentine doublecycle structured watercooling tube arrangement is used to increase cooling efficiency. Sprinklers are used to spray and moisturize the concrete surface. Control units based on microcontrollers are independent of each other, collecting data to control the process of water cooling and moisturizing, and communicate with industrial computer via LoRa IoT (Long Range Radio Internet of Things). Control units collect sensor data via ITU bus and RS485 bus. The start and stop of water pipe cooling and spray moisturizing are controlled by control units through butterfly valves. The system adopts efficient hardware and software structure, uses different communication strategy. In application experiments, the control system can effectively improve the efficiency of water pipe cooling and spray moisturization.

Accurate Pouring using Model Predictive Control Enabled by Recurrent Neural Network Humans perform the task of pouring often and in which exhibit consistent accuracy regardless of the complicated dynamics of the liquid. Model predictive control (MPC) appears to be a natural candidate solution for the task of accurate pouring considering its wide use in industrial applications. However, MPC requires the model of the system in question. Since an accurate model of the liquid dynamics is difficult to obtain, the usefulness of MPC for the pouring task is uncertain. In this work, we model the dynamics of water using a recurrent neural network (RNN), which enables the use of MPC for pouring control. We evaluated our RNNenabled MPC controller using a physical system we made ourselves and averaged a pouring error of 16. 4mL over 5 different source containers. We also compared our controller with a baseline switch controller and showed that our controller achieved a much higher accuracy than the baseline controller.