LEADER 04280nam 2200697Ia 450 001 9910828588503321 005 20200520144314.0 010 $a0-429-13987-X 010 $a1-283-34982-5 010 $a9786613349828 010 $a1-4200-7559-4 024 7 $a10.1201/b11224 035 $a(CKB)2550000000062784 035 $a(EBL)1446468 035 $a(SSID)ssj0000565555 035 $a(PQKBManifestationID)11319162 035 $a(PQKBTitleCode)TC0000565555 035 $a(PQKBWorkID)10533144 035 $a(PQKB)10886715 035 $a(Au-PeEL)EBL1446468 035 $a(CaPaEBR)ebr10508919 035 $a(CaONFJC)MIL334982 035 $a(OCoLC)763161395 035 $a(OCoLC)762324952 035 $a(CaSebORM)9781420075595 035 $a(MiAaPQ)EBC1446468 035 $a(EXLCZ)992550000000062784 100 $a20111021d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIndustrial control systems $emathematical and statistical models and techniques /$fAdedeji B. Badiru, Oye Ibidapo-Obe, Babatunde J. Ayeni 205 $a1st ed. 210 $aBoca Raton $cCRC Press$dc2012 215 $a1 online resource (374 p.) 225 1 $aIndustrial innovation 300 $aDescription based upon print version of record. 311 $a1-4200-7558-6 320 $aIncludes bibliographical references. 327 $aFront 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 formulae 327 $aBack Cover 330 $aPreface This book presents the mathematical foundation for building and implementing industrial control systems. It contains mathematically rigorous models and techniques for control systems, in general, with specific orientation toward industrial systems. Industrial control encompasses several types of control systems. Some common elements of industrial control systems include supervisory control and data acquisition systems, distributed control systems, and other generic control system configurations, such as programmable logic controllers, that are often found in industrial operations and engineering infrastructure. Industrial control systems are not limited to production or manufacturing enterprises, as they are typically used in general industries such as electrical, water, oil and gas, and data acquisition devices. Based on information received from remote sensors, automated commands can be sent to remote control devices, which are referred to as field devices. Field devices are used to control local operations. These may include opening and closing valves, tripping breakers, collecting data from sensors, and monitoring local operating conditions. All of these are governed by some form of mathematical representation. Thus, this book has great importance in linking theory and practice. Distributed control systems are used to control industrial processes such as electric power generation, oil and gas refineries, water and wastewater treatment, and chemical, food, and automotive production. --$cProvided by publisher. 410 0$aIndustrial innovation series. 606 $aProcess control$xMathematical models 606 $aProcess control$xStatistical methods 615 0$aProcess control$xMathematical models. 615 0$aProcess control$xStatistical methods. 676 $a658.5072/7 686 $aTEC016000$aTEC009000$aTEC007000$2bisacsh 700 $aBadiru$b Adedeji Bodunde$f1952-$027420 701 $aAyeni$b Babatunde J$01629998 701 $aIbidapo-Obe$b Oye$01629997 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828588503321 996 $aIndustrial control systems$93968054 997 $aUNINA