04262oam 2200685I 450 991082858850332120200520144314.00-429-13987-X1-283-34982-597866133498281-4200-7559-410.1201/b11224 (CKB)2550000000062784(EBL)1446468(SSID)ssj0000565555(PQKBManifestationID)11319162(PQKBTitleCode)TC0000565555(PQKBWorkID)10533144(PQKB)10886715(Au-PeEL)EBL1446468(CaPaEBR)ebr10508919(CaONFJC)MIL334982(OCoLC)763161395(OCoLC)762324952(CaSebORM)9781420075595(MiAaPQ)EBC1446468(EXLCZ)99255000000006278420180331d2012 uy 0engur|n|---|||||txtccrIndustrial control systems mathematical and statistical models and techniques /Adedeji B. Badiru, Oye Ibidapo-Obe, Babatunde J. AyeniBoca Raton :CRC Press,2012.1 online resource (374 p.)Industrial innovationDescription based upon print version of record.1-4200-7558-6 Includes bibliographical references.Front Cover; Contents; Preface; Acknowledgments; Authors; Chapter 1: Mathematical modeling for product design; Chapter 2: Dynamic fuzzy systems modeling; Chapter 3: Stochastic systems modeling; Chapter 4: Systems optimization techniques; Chapter 5: Statistical control techniques; Chapter 6: Design of experiment techniques; Chapter 7: Risk analysis and estimation techniques; Chapter 8: Mathematical modeling and control of multi- constrained projects; Chapter 9: Online support vector regression with varying parameters for time-dependent data; Appendix: Mathematical and engineering formulaeBack CoverPreface This book presents the mathematical foundation for building and implementing industrial control systems. It contains mathematically rigorous models and techniques for control systems, in general, with specific orientation toward industrial systems. Industrial control encompasses several types of control systems. Some common elements of industrial control systems include supervisory control and data acquisition systems, distributed control systems, and other generic control system configurations, such as programmable logic controllers, that are often found in industrial operations and engineering infrastructure. Industrial control systems are not limited to production or manufacturing enterprises, as they are typically used in general industries such as electrical, water, oil and gas, and data acquisition devices. Based on information received from remote sensors, automated commands can be sent to remote control devices, which are referred to as field devices. Field devices are used to control local operations. These may include opening and closing valves, tripping breakers, collecting data from sensors, and monitoring local operating conditions. All of these are governed by some form of mathematical representation. Thus, this book has great importance in linking theory and practice. Distributed control systems are used to control industrial processes such as electric power generation, oil and gas refineries, water and wastewater treatment, and chemical, food, and automotive production. --Provided by publisher.Industrial innovation series.Process controlMathematical modelsProcess controlStatistical methodsProcess controlMathematical models.Process controlStatistical methods.658.5072/7TEC016000TEC009000TEC007000bisacshBadiru Adedeji Bodunde1952,27420Ibidapo-Obe Oye1629997Ayeni Babatunde J1629998MiAaPQMiAaPQMiAaPQBOOK9910828588503321Industrial control systems3968054UNINA