The article surveys the drying of solids materials and polymer solutions when infrared radiation (IR) is employed as the main heating source. The study reviews the current research trends of IR drying of specific applications. A case study similar to an industrial setting is presented to illustrate a model development and control scheme of an IR drying unit. The design and online implementation of an internal model controller (IMC) is discussed. The study demonstrates the controller capabilities to suppress random variations of the moisture content in the material entering the dryer. Simulation results also showed the success of model predictive control (MPC) multivariable controller ability, while handling process interactions and process constraints, to track setpoint changes in the humidity and temperature of the material exiting the dryer and to reject unmeasured stochastic disturbances in the inlet humidity stream.

Low-density polyethylene (LDPE) is a very important polymer, which is usually produced through a free radical polymerization process in high-pressure tubular reactors. In this study, the mathematical model of this process is developed on the basis of a comprehensive reaction mechanism to accurately determine polymerization rate, and polymer properties under extreme temperature conditions. The model comprises of (i) the mass balances of monomer, initiator, solvent, live radicals and dead polymer chains, and (ii) the energy balances of a tubular LDPE reactor, and its jacket under steady state condition. The model considers the variations in the density and viscosity of reactants along reactor length. Computer simulation of the model is successfully carried out to accurately describe the performance of a non-isothermal, high-pressure, industrial LDPE reactor with multiple initiator injections. Based on the developed non-linear model, the optimal control of the industrial reactor is carried out using genetic algorithms to maximize monomer conversion using jacket temperature as a control function of reactor length. The application of optimal control leads to significant improvements in the final monomer conversion, and capacity utilization of the reactor.

Polyvinyl alcohol (PVA) is an emerging pollutant commonly found in industrial wastewater, owing to its extensive usage as an additive in the manufacturing industry. PVA’s popularity has made wastewater treatment technologies for PVA degradation a popular research topic in industrial wastewater treatment. Although many PVA degradation technologies are studied in bench-scale processes, recent advancements in process optimization and control of wastewater treatment technologies such as advanced oxidation processes (AOPs) show the feasibility of these processes by monitoring and controlling processes to meet desired regulatory standards. These wastewater treatment technologies exhibit complex reaction mechanisms leading to nonlinear and nonstationary behavior related to variability in operational conditions. Thus, black-box dynamic modeling is a promising tool for designing control schemes since dynamic modeling is more complicated in terms of first principles and reaction mechanisms. This study seeks to provide a survey of process control methods via a comprehensive review focusing on PVA degradation methods, including biological and advanced oxidation processes, along with their reaction mechanisms, control-oriented dynamic modeling (i.e., state-space, transfer function, and artificial neural network modeling), and control strategies (i.e., proportional-integral-derivative control and predictive control) associated with wastewater treatment technologies utilized for PVA degradation.