The main objective of this book is to provide methods of designing for stable CSTR and unstable CSTR with time delay and with or without positive or negative zero. The methods consist of synthesis method and IMC method. Simulation examples on various transfer functions models model relating concentration of the product to the feed flow rate in isothermal CSTR carrying out Van de Vusse reaction, transfer function model relating the reactor temperature to jacket temperature in jacketed CSTR, transfer function model relating concentration of the cells to the dilution rate in bioreactors and transfer function relating temperature of incinerator to the inlet load rate in municipal waste incinerator are given to show the effectiveness of the proposed methods. Many recycle processes where energy and mass recycle takes place are represented by SOPTDZ transfer function model.
Continuous stirred tank reactor is a typical chemical reactor with complex non linear dynamic characteristics. There has been considerable interest in its state estimation and real time control based on mathematical modeling. However, the lack of understanding of the dynamics of the process, the highly sensitive and non linear behavior of the reactor, has made it difficult to develop the precise mathematical modeling of the system. Efficient control of the product concentration in CSTR can be achieved only through accurate model. Here attempts are made to ease the modeling difficulties using AI techniques such as Fuzzy logic. Simulation results demonstrate the effectiveness of Fuzzy logic control technique. The system is a stirred tank reactor with two flows of liquid enter the system and another flow exits the tank with the formation of product. Simulink was employed to design a model for this system in the simulation environment. This work is aimed for utilization by researchers, industrialists’ and students. Furthermore it will be especially relevant and useful for the students of Electrical Engg. and Chemical Engg. for carrying out research in the area of simulation of CSTR.
In spite of continuing advances in optimal solution techniques for optimization and control problems, many practical combinatorial problems remain too large or too complex to be solved by these known techniques. Thus, a heuristic approach (Neural Network Model) is often the only viable alternative. Neural Network Models offer the most unified approach to building truly intelligent systems which can provide good optimal solution for many applications. In this work we propose a hybrid (Kalkoh) neural network algorithm which is being used to model and solve the continuous stirred tank mixer (CSTM) problem. The hybrid algorithm is robust and converges fast without being trapped into a local minimal as is the case with the popular back-propagation neural network. The characteristic equations governing the dynamics of the Continuous Stirred Tank Mixer/Reactor and the controller were formulated and tested and found to be consistently stable.
Oscillatory baffled reactors are plug flow reactors, where tubes fitted with orifice plate baffles superimpose an oscillatory motion upon the net flow. The interaction of the baffles with the process fluid generates uniform mixing and enhanced transport rates, whilst maintaining plug flow conditions. Unlike conventional tubular reactors, where a minimum Reynolds number must be maintained, the tube-side mixing is independent of any net flow allowing long residence times to be achieved in a reactor of reduced length-to-diameter ratio leading to much more compact designs. This suggests a niche application in converting long reactions from batch to continuous processing. Since the major advantages of the OBR are its uniform, controllable mixing, which can enhance gas-liquid mass transfer, and lower, more uniform shear rates than in a stirred tank reactor, it should be suitable to intensify biological reactions. In this work two different fermentation systems were studied, firstly, the fermentation stage of the beer production process, secondly, the production of biopolymers by Pseudomonas putida KT2442, to investigate the possibility of process intensification in biological systems.
This book is a reference source on evaluate of the performance of the anaerobic migrating blanked reactor (AMBR) and anaerobic baffled reactor (ABR) in the treatment of nitroorganic compounds. This book consists of five chapters. Chapter One – Introduction : The Objective and Scope of the Study, The Novelties of the Study; Chapter Two - Literature Review: Nitroaromatic Compounds, Anaerobic Baffled Reactor (ABR), Anaerobic Migrating Blanked Reactor (AMBR); Chapter Three - Materials and Methods: Experimental System, Seed of Reactors, Analytical Methods, Operation Conditions, Kinetic Approaches in Anaerobic Continuous Studies; Chapter Four - Results and Discusions: Batch Studies, Continuous Studies, Determination of Kinetic Constants, Process Economy; Chapter Five - Conclusions
Batch and semi-batch reactors are used in the manufacture of low-volume high-value chemicals, where even a marginal increase in product yield can lead to considerably higher profits. Most of the present optimization and model based control schemes for semi-batch reactors are based on mechanistic models, whose development is a difficult and time- consuming exercise. Therefore, this book provides a new data driven approach for modeling, trajectory optimization and tracking of semi-batch reactors based on parameterization of input and output trajectories using orthonormal polynomials, and development of an artificial neural network model relating them using information available in historical databases. The generated optimal set point trajectories are tracked by developing data driven versions of generic model control. Simulation studies on semi-batch reactors illustrate their applicability. This can be useful to academic researchers working on data-driven modeling and optimization of batch processes and to industrial readers to explore the possibility of achieving better operational policies based on their historic operating data.
This thesis analyses the working of sewage farms and brings out its similarities with constructed wetlands in its functioning as a low-cost waste treatment and resource recovery facility. A mathematical model is developed for evaluating the treatment potential of sewage farms/constructed wetlands for the BOD removal by assuming it as made up of a number of continuous flow stirred tank reactors (CFSTRs) in series. In order to improve the accuracy of predictive equations, provisions were made to take into account the effect of evaporation and evapotranspiration losses. The proposed model was validated against measured values of BOD removal from a constructed wetland at Listowel, Canada (summer) and compared with the simulated results using the other models such as USEPA (1988), Chen et al. (1999) and Vogeler and Scherfig (2000). In order to further ascertain the validity of the proposed model it is applied for the sewage farm froma a typical south Indian city of Madurai. In the light of the available literature and the findings from the present study, a design procedure and guidelines are proposed for the design of sewage farms/constructed wetlands at the end of the study.
The automatic process control has made tremendous advances in last three decades with the advent of computer control of complex processes. However, fault-tolerant control that is a very important task in managing process plants still remains largely a manual activity and a component failure is accommodated for by one or several identical component backups. For sensor failure case, analytical redundancy is often introduced that consists of the use of state estimation schemes capable of replacing a faulty sensor. The estimator is MRAN, the recently developed algorithm for RBF neural networks, has online learning algorithm and can be used for nonlinear time-varying dynamics. This is in comparison with other observers and filters used for low-order LTI systems. The different types of sensor failures that are artificially injected into an exothermic continuous stirred tank reactor (CSTR) with highly nonlinear dynamics are tested and evaluated in the SIMULINK programming environment in the closed loop condition.