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The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ..., new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The water and wastewater industry has undergone many changes in recent years. Of particular importance has been a renewed emphasis on improving resource management with tighter regulatory controls setting new targets on pricing, industry efficiency and loss reduction for both water and wastewater with more stringent environmental discharge conditions for wastewater. Meantime, the demand for water and wastewater services grows as the population increases and wishes for improved living conditions involving, among other items, domestic appliances that use water. Consequently, the installed infrastructure of the industry has to be continuously upgraded and extended, and employed more effectively to accommodate the new demands, both in throughput and in meeting the new regulatory conditions. Investment in fixed infrastructure is capital-intensive and slow to come on-stream. One outcome of these changes and demands is that the industry is examining the potential benefits of, and in many cases using, more advanced control systems.
Membrane bioreactor (MBR) technology is a wastewater treatment method combining biological pollutant treatment with physical membrane separation. It has gained increasing commercial significance over the last decade, with applications in municipal and industrial wastewater treatment becoming increasingly widespread. This book covers a wide variety of MBR topics, including filtration theory, membrane materials and geometry, fouling phenomena and properties, and strategies for minimizing fouling. Also covered are practical aspects such as operation, maintenance, design, and application.
The objective of any chemical process is to transform raw materials into more valuable products subject to not only physical and environmental but also economic and safety constraints. To meet all these constraints in the presence of disturbances the processes must be controlled. Although nowadays there are many available control techniques available Model Predictive Control (MPC) is widely used in industry due to its many advantages such as optimal handling of interactions in multivariable systems and process constraints. Generally, the MPC strategy is implemented within a hierarchical structure, where it receives set points or targets from the Real Time Optimization (RTO) layer and then maintains the process at these targets by calculating optimal control moves. However, often the set point from the RTO may not be the best optimal operation or it may not be reachable thus motivating the integration of the RTO and MPC calculations into one single computation layer. This work focuses on this idea of integrating RTO and MPC into one single optimization problem thus resulting in an approach referred in literature as Economic Model Predictive Control (EMPC). The term “Economic” is used to reflect that the objective function used for optimization includes an economic objective generally used in RTO calculations. In this thesis, we propose an EMPC algorithm which calculates manipulated variables values to optimize an objective consisting of a combination of a steady state and a dynamic economic cost. A weight factor is used to balance the contributions of each of these two terms. Also, the cost is defined such as when the best economic steady state is reached the objective is only influenced by the dynamic economic cost. An additional feature of the proposed algorithm is that the asymptotic stability is satisfied online by enforcing four especial constraints within the optimization problem: 1-positive definiteness of the matrix P defining the Lyapunov function, 2- contraction of the Lyapunov function with respect to set point changes, 3- contraction of the matrix P with respect to time and 4- Lyapunov stability condition. The last constraint both ensures decreasing of the Lyapunov function and also accounts for the robustness of the algorithm with respect to model error (uncertainty). A particular novelty of this algorithm is that it constantly calculates a best set point with respect to which stability is ensured by the aforementioned constraints. In contrast to other algorithms reported in the literature, the proposed algorithm does not require terminal constraints or terms in the cost that penalize deviations from fixed set points that often lead to conservative closed loop performance. To account for unmeasured disturbances entering the process, changes in parameters are also explored and the algorithm is devised to compensate for these changes through parameter updating. Accordingly, the parameters are included as additional decision variables within the optimization problem without the need for an external observer. The stability of the parameters estimation is ensured through the set point constraint mentioned above. To demonstrate the capabilities of the proposed algorithm, it is tested on two case studies: a simpler one involving a system of 4 nonlinear ODEs describing an isothermal nonlinear reactor and a larger problem involving a non-isothermal Williams-Otto reactor with parallel reactions. The dynamics of the latter reactor consists of a set of nonlinear ODE describing the evolution of the process temperature and concentration of the different species. The simulations for the isothermal reactor showed that the proposed algorithm not only outperformed (in terms of an economic function) alternative formulations, but addressed all their limitations. In addition, when there was a parameter modification, this was adapted in a finite time. In terms of the non-isothermal reactor, the simulations demonstrated that not only the best steady state could be computed, but also the states were steered to it satisfying the online stability property.
The book covers the subject of membrane bioreactors (MBR) for wastewater treatment, dealing with municipal as well as industrial wastewaters. The book details the 3 types of MBR available and discusses the science behind the technology, their design features, operation, applications, advantages, limitations, performance, current research activities and cost. As the demand for wastewater treatment, recycling and re-use technologies increases, it is envisaged that the membrane separation bioreactor will corner the market. Contents Membrane Fundamentals Biological Fundamentals Biomass Separation Membrane Bioreactors Membrane Aeration and Extractive Bioreactors Commercial Membrane Bioreactor Systems Membrane Bioreactor Applications Case Studies
Recent technical innovations and significant cost reductions have sharply increased the potential for using Membrane Bioreactor (MBR) technology in municipal wastewater treatment. MBR technology displays several advantages compared to the traditional activated sludge processes, such as high effluent quality, limited space requirement and with the possibility of a flexible and phased extension of existing waste water treatment plants. Membrane Bioreactors for Municipal Wastewater Treatment describes the results of a comparative research programme involving four leading membrane suppliers: Kubota (Japan), Mitsubishi (Japan), X-Flow (Netherlands) and Zenon (Canada). Each supplier provided a pilot to represent a suitable scale - right up to full scale. These pilots were operated and optimised in the course of the research programme to achieve the best operating window under different operating regimes. The research focussed on the functionality of the membrane, the biological treatment, membrane fouling, achieved effluent quality, and system operability as well as other factors. In a number of side studies the required pre-treatment, membrane fouling/cleaning, energy usage, effluent quality and sludge processing were also addressed. The comparative pilot research was carried out by DHV Water on location at the wastewater treatment plant at Beverwijk in the Netherlands.
The present Special Issue brings together recent research findings from renowned scientists in the field of water treatment and assembled contributions on advanced technologies applied to the treatment of wastewater and drinking water, with emphasis on novel membrane treatment technologies. 12 research contributions have highlighted various processes and technologies, which can achieve effective treatment and purification of wastewater and of drinking water, aiming (occasionally) for water reuse. The main topics which are analyzed are the use of novel type membranes in bioreactors, the use of modified membranes, for example using vacuum membrane distillation, the fouling of membranes, the problem of arsenic, antimony and chromium contamination in groundwaters and its removal and the use of novel technologies for more efficient ozonation.
The MBR market continues to experience a massive growth. The best practice in the field is constantly changing and unique quality requirements and management issues are regularly emerging. The second edition of Membrane Biological Reactors: Theory, Modeling, Design, Management and Applications to Wastewater Reuse comprehensively covers the salient features and emerging issues associated with the MBR technology. The book provides thorough coverage starting from biological aspects and fundamentals of membranes, via modeling and design concepts, to practitioners’ perspective and good application examples. In the second edition, the chapters have been updated to cover the recently emerged issues. Particularly, the book presents the current status of the technology including market drivers/ restraints and development trend. Process fundamentals (both the biological and membrane components) have received in-depth coverage in the new edition. A new chapter has been added to provide a stronger focus on reuse applications in general and the decisive role of MBR in the entire reuse chain. The second edition also comes with a new chapter containing practical design problems to complement the concepts communicated throughout the book. Other distinguishing features of the new edition are coverage of novel developments and hybrid processes for specialised wastewaters, energy efficiency and sustainability of the process, aspects of MBR process automation and recent material on case studies. The new edition is a valuable reference to the academic and professional community and suitable for undergraduate and postgraduate teaching in Environmental Engineering, Chemical Engineering and Biotechnology.
The chemical industry is a vital sector of the US economy. Maintaining optimal chemical process operation is critical to the future success of the US chemical industry on a global market. Traditionally, economic optimization of chemical processes has been addressed in a two-layer hierarchical architecture. In the upper layer, real-time optimization carries out economic process optimization by computing optimal process operation set-points using detailed nonlinear steady-state process models. These set-points are used by the lower layer feedback control systems to force the process to operate on these set-points. While this paradigm has been successful, we are witnessing an increasing need for dynamic market and demand-driven operations for more efficient process operation, increasing response capability to changing customer demand, and achieving real-time energy management. To enable next-generation market-driven operation, economic model predictive control (EMPC), which is an model predictive control scheme formulated with a stage cost that represents the process economics, has been proposed to integrate dynamic economic optimization of processes with feedback control. Motivated by these considerations, novel theory and methods needed for the design of computationally tractable economic model predictive control systems for nonlinear processes are developed in this dissertation. Specifically, the following considerations are addressed: a) EMPC structures for nonlinear systems which address: infinite-time and finite-time closed-loop economic performance and time-varying economic considerations such as changing energy pricing; b) two-layer (hierarchical) dynamic economic process optimization and feedback control frameworks that incorporate EMPC with other control strategies allowing for computational efficiency; and c) EMPC schemes that account for real-time computation requirements. The EMPC schemes and methodologies are applied to chemical process applications. The application studies demonstrate the effectiveness of the EMPC schemes to maintain process stability and improve economic performance under dynamic operation as well as to increase efficiency, reliability and profitability of processes, thereby contributing to the vision of Smart Manufacturing.