Dynamic process modeling and hybrid intelligent control of ethylene copolymerization in gas phase catalytic fluidized bed reactors

BACKGROUND: Polyethylene (PE) is the most extensively consumed plastic in the world, and gas phase‐based processes are widely used for its production owing to their flexibility. The sole type of reactor that can produce PE in the gas phase is the fluidized bed reactor (FBR), and effective modeling and control of FBRs are of great importance for design, scale‐up and simulation studies. This paper discusses these issues and suggests a novel advanced control structure for these systems. RESULTS: A unified process modeling and control approach is introduced for ethylene copolymerization in FBRs. The results show that our previously developed two‐phase model is well confirmed using real industrial data and is exact enough to further develop different control strategies. It is also shown that, owing to high system nonlinearities, conventional controllers are not suitable for this system, so advanced controllers are needed. Melt flow index (MFI) and reactor temperature are chosen as vital variables, and intelligent controllers were able to sufficiently control them. Performance indicators show that advanced controllers have a superior performance in comparison with conventional controllers. CONCLUSION: Based on control performance indicators, the adaptive neuro‐fuzzy inference system (ANFIS) controller for MFI control and the hybrid ANFIS–proportional‐integral‐differential (PID) controller for temperature control perform better regarding disturbance rejection and setpoint tracking in comparison with conventional controllers. © 2019 Society of Chemical Industr

Dynamic hybrid simulation of batch processes driven by a scheduling module

Simulation is now a CAPE tool widely used by practicing engineers for process design and control. In particular, it allows various offline analyses to improve system performance such as productivity, energy efficiency, waste reduction, etc. In this framework, we have developed the dynamic hybrid simulation environment PrODHyS whose particularity is to provide general and reusable object-oriented components dedicated to the modeling of devices and operations found in chemical processes. Unlike continuous processes, the dynamic simulation of batch processes requires the execution of control recipes to achieve a set of production orders. For these reasons, PrODHyS is coupled to a scheduling module (ProSched) based on a MILP mathematical model in order to initialize various operational parameters and to ensure a proper completion of the simulation. This paper focuses on the procedure used to generate the simulation model corresponding to the realization of a scenario described through a particular scheduling

Catalytic-Dielectric Barrier Discharge Plasma Reactor For Methane and Carbon Dioxide Conversion

A catalytic - DBD plasma reactor was designed and developed for co-generation of synthesis gas and C2+ hydrocarbons from methane. A hybrid Artificial Neural Network - Genetic Algorithm (ANN-GA) was developed to model, simulate and optimize the reactor. Effects of CH4/CO2 feed ratio, total feed flow rate, discharge voltage and reactor wall temperature on the performance of catalytic DBD plasma reactor was explored. The Pareto optimal solutions and corresponding optimal operating parameters ranges based on multi-objectives can be suggested for catalytic DBD plasma reactor owing to two cases, i.e. simultaneous maximization of CH4 conversion and C2+ selectivity, and H2 selectivity and H2/CO ratio. It can be concluded that the hybrid catalytic DBD plasma reactor is potential for co-generation of synthesis gas and higher hydrocarbons from methane and carbon dioxide and showed better than the conventional fixed bed reactor with respect to CH4 conversion, C2+ yield and H2 selectivity for CO2 OCM process

Nonlinear model predictive control for hydrogen production in an ethanol steam reformer with membrane separation

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper presents a new Nonlinear Model Predictive Control (NMPC) design for an Ethanol Steam Reformer with Pd-Ag membrane separation stage. The reformer is used to produce pure hydrogen able to feed a Proton Exchange Membrane Fuel Cell. Mass and energy balances are used to obtain the nonlinear dynamic model of both the reforming and the separation stages. Constraints, system nonlinearities and flexible cost function are the main reasons to select an NMPC controller, which is tested against the ordinary differential equations as simulation model, and has an internal model based on the sample data technique.Accepted versio

Predictive functional control for the temperature control of a chemical batch reactor

A predictive functional control (PFC) technique is applied to the temperature control of a pilot-plant batch reactor equipped with a mono-fluid heating/cooling system. A cascade control structure has been implemented according to the process sub-units reactor and heating/cooling system. Hereby differences in the sub-units dynamics are taken into consideration. PFC technique is described and its main differences with a standard model predictive control (MPC) technique are discussed. To evaluate its robustness, PFC has been applied to the temperature control of an exothermic chemical reaction. Experimental results show that PFC enables a precise tracking of the set-point temperature and that the PFC performances are mainly determined by its internal dynamic process model. Finally, results show the performance of the cascade control structure to handle different dynamics of the heating/cooling system

Modeling of the oxy-combustion calciner in the post-combustion calcium looping process

The calcium looping process is a fast-developing post-combustion CO2 capture technology in which combustion flue gases are treated in two interconnected fluidized beds. CO2 is absorbed from the flue gases with calcium oxide in the carbonator operating at 650 ºC. The resulting CaCO3 product is regenerated into CaO and CO2 in the calciner producing a pure stream of CO2. In order to produce a suitable gas stream for CO2 compression, oxy-combustion of a fuel, such as coal, is required to keep the temperature of the calciner within the optimal operation range of 880-920°C. Studies have shown that the calcium looping process CO2 capture efficiencies are between 70 % and 97 %. The calciner reactor is a critical component in the calcium looping process. The operation of the calciner determines the purity of gases entering the CO2 compression. The optimal design of the calciner will lower the expenses of the calcium looping process significantly. Achieving full calcination at the lowest possible temperature reduces the cost of oxygen and fuel consumption. In this work, a 1.7 MW pilot plant calciner was studied with two modeling approaches: 3-D calciner model and 1-D process model. The 3-D model solves fundamental balance equations for a fluidized bed reactor operating under steady-state condition by applying the control volume method. In addition to the balance equations, semiempirical models are used to describe chemical reactions, solid entrainment and heat transfer to reduce computation effort. The input values of the 3-D-model were adjusted based on the 1-D-model results, in order to model the behavior of the carbonator reactor realistically. Both models indicated that the calcination is very fast in oxy-fuel conditions when the appropriate temperature conditions are met. The 3-D model was used to study the sulfur capture mechanisms in the oxy-fired calciner. As expected, very high sulfur capture efficiency was achieved. After confirming that the 1-D model with simplified descriptions for the sorbent reactions produces similar results to the more detailed 3-D model, the 1-D model was used to simulate calcium looping process with different recirculation ratios to find an optimal area where the fuel consumption is low and the capture efficiency is sufficiently high. It was confirmed that a large fraction of the solids can be recirculated to both reactors to achieve savings in fuel and oxygen consumption before the capture efficiency is affected in the pilot unit. With low recirculation ratios the temperature difference between the reactors becomes too low for the cyclic carbonation and calcination. As a general observation, the small particle size creates high solid fluxes in the calcium looping process that should be taken into account in the design of the system