000 04017nam a22004455i 4500
001 978-1-84996-353-4
003 DE-He213
005 20140220084516.0
007 cr nn 008mamaa
008 100930s2010 xxk| s |||| 0|eng d
020 _a9781849963534
_9978-1-84996-353-4
024 7 _a10.1007/978-1-84996-353-4
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aOcampo-Martinez, Carlos.
_eauthor.
245 1 0 _aModel Predictive Control of Wastewater Systems
_h[electronic resource] /
_cby Carlos Ocampo-Martinez.
264 1 _aLondon :
_bSpringer London,
_c2010.
300 _aXXX, 217p. 69 illus., 21 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Industrial Control,
_x1430-9491
505 0 _aBackground 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 _aSewer 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 _aEngineering.
650 0 _aEnvironmental pollution.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781849963527
830 0 _aAdvances in Industrial Control,
_x1430-9491
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-84996-353-4
912 _aZDB-2-ENG
999 _c111022
_d111022