Model Predictive Control of Wastewater Systems

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Ocampo-Martinez, Carlos (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London, 2010.
Σειρά:Advances in Industrial Control,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Ocampo-Martinez, Carlos.  |e author. 
245 1 0 |a Model Predictive Control of Wastewater Systems  |h [electronic resource] /  |c by Carlos Ocampo-Martinez. 
264 1 |a London :  |b Springer London,  |c 2010. 
300 |a XXX, 217 p.  |b online resource. 
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490 1 |a Advances in Industrial Control,  |x 1430-9491 
505 0 |a Background and Case Study Modelling -- Background -- Principles of the Mathematical Modelling of Sewer Networks -- Model Predictive Control of Sewer Networks -- Formulating the Model Predictive Control Problem -- Predictive Control Problem Formulation and Hybrid Systems -- Suboptimal Hybrid Model Predictive Control -- Fault-tolerance Capabilities of Model Predictive Control -- Model Predictive Control and Fault Tolerance -- Fault-tolerance Evaluation of Actuator Fault Configurations -- Concluding Remarks -- Concluding Remarks. 
520 |a 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 algorithms they employ. 
650 0 |a Engineering. 
650 0 |a Water-supply. 
650 0 |a Control engineering. 
650 0 |a Water pollution. 
650 1 4 |a Engineering. 
650 2 4 |a Control. 
650 2 4 |a Water Industry/Water Technologies. 
650 2 4 |a Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781849963527 
830 0 |a Advances in Industrial Control,  |x 1430-9491 
856 4 0 |u http://dx.doi.org/10.1007/978-1-84996-353-4  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)