IoT-Based Model Predictive Control Architecture for HVAC Systems and a Comprehensive Study of Security Issues of 5G and IoT

Abstract

AbstractThis chapter addresses predictive control for HVAC systems. One of the major radical control techniques is the model predictive control for the difficult multivariate control issues. The existing time slots are optimized by model predictive control (MPC), but it keeps potential time slots in mind. By forecasting potential incidents, it is universally applied as digital control and can take control steps accordingly. One of the modes of model predictive control is stochastic model predictive control. Ambiguity is in attendance in many control manufacturing issues and is also present in a broader class of applications. It utilizes stochastic climate and load data collected starting from previous past data and minimizes the standard energy cost while reducing the chance of comfort breaches. One way to solve stochastic model predictive control (SMPC) is to explain when ambiguity is assumed to be chance and not consistent, the dispersion of unknown model parameters. Various forms of model predictive control and HVAC in the perspective of MPC, IoT-based architecture for HVAC, and a comprehensive study of security issues of 5G and IoT will be discussed in this chapter.KeywordsHeatVentilation and air conditioning (HVAC)Predictive control model (MPC)Stochastic model predictive control (SMPC)Robust model predictive control (RMPC)Non-linear model predictive control (NMPC)Explicit model predictive control (eMPC)IoT5GGeneralized predictive controlModels Gray-boxBlack-box modelsLinear time invariantSemi-deterministic physical modellingCalibrated simulation models