Model Predictive Control of Wastewater Systems (Advances in Industrial Control) - Softcover

Ocampo-Martinez, Carlos

Softcover

ISBN 10: 1447157184 ISBN 13: 9781447157182

Publisher: Springer, 2014

Synopsis

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.

About this title

From the Back Cover

Sewer networks are large-scale systems with many variables, complex dynamics and strongly nonlinear behaviour. Their control plays a fundamental role in the management of hydrological systems related to the natural water cycle, potentially avoiding flooding and sewer overflow in extreme weather. An adequate control scheme must deal with the complicated nature of sewer networks.

Model Predictive Control of Wastewater Systems shows how sewage systems can be modelled and controlled within the framework of model predictive control (MPC). Several MPC-based strategies are proposed, accounting for the inherently complex dynamics and the multi-objective nature of the control required. The effect of system disturbance, represented by data from real rain episodes, on the performance of the control loop to which these strategies give rise is also accommodated. Complementary to these considerations is the incorporation of the closed-loop system within a fault-tolerant architecture and the study of faults in system actuators. Actuator faults are represented using hybrid modelling techniques, avoiding the loss of convexity of the related optimisation problem when the linear case is considered. The methods and control designs described in this book can easily be extrapolated to other complex systems of similar nature such as drinking-water networks and irrigation canals. A MATLAB^® toolbox, created by the author and available for download from www.springer.com/ISBN will assist readers in implementing the MPC methods described within a sewer network.

Model Predictive Control of Wastewater Systems will be of interest to academic researchers working with large-scale and complex systems and studying the applications of model-predictive, hybrid and fault-tolerant control. Control engineers employed in industries associated with water management will find this book a most useful resource for suggesting improvements in the control algorithmsthey employ.

Edition details

• Publisher: Springer
• Publication date: 2014
• Language: English
• ISBN 10: 1447157184
• ISBN 13: 9781447157182
• Binding: Paperback
• Number of pages: 247