LEADER 04356nam 22005775 450 001 9910484710803321 005 20200705163258.0 010 $a3-030-04140-9 024 7 $a10.1007/978-3-030-04140-3 035 $a(CKB)4100000007181228 035 $a(MiAaPQ)EBC5607450 035 $a(DE-He213)978-3-030-04140-3 035 $a(PPN)243769784 035 $a(EXLCZ)994100000007181228 100 $a20181128d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModeling and Control of Batch Processes $eTheory and Applications /$fby Prashant Mhaskar, Abhinav Garg, Brandon Corbett 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (346 pages) 225 1 $aAdvances in Industrial Control,$x1430-9491 311 $a3-030-04139-5 327 $aMotivation -- Part I: First-Principles Model Based Control -- Part II: Integrating Multi-Model Dynamics With PLS Based Approaches -- Part III: Subspace Identification Based Modeling Approach for Batch Processes. 330 $aModeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods are specifically tailored to handle issues pertinent to batch processes, such as nonlinear dynamics and lack of online quality measurements. In particular, the book proposes: a novel batch control design with well characterized feasibility properties; a modeling approach that unites multi-model and partial least squares techniques; a generalization of the subspace identification approach for batch processes; and applications to several detailed case studies, ranging from a complex simulation test bed to industrial data. The book?s proposed methodology employs statistical tools, such as partial least squares and subspace identification, and couples them with notions from state-space-based models to provide solutions to the quality control problem for batch processes. Practical implementation issues are discussed to help readers understand the application of the methods in greater depth. The book includes numerous comments and remarks providing insight and fundamental understanding into the modeling and control of batch processes. Modeling and Control of Batch Processes includes many detailed examples of industrial relevance that can be tailored by process control engineers or researchers to a specific application. The book is also of interest to graduate students studying control systems, as it contains new research topics and references to significant recent work. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control. 410 0$aAdvances in Industrial Control,$x1430-9491 606 $aAutomatic control 606 $aIndustrial engineering 606 $aProduction engineering 606 $aChemical engineering 606 $aControl and Systems Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/T19010 606 $aIndustrial and Production Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T22008 606 $aIndustrial Chemistry/Chemical Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/C27000 615 0$aAutomatic control. 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 0$aChemical engineering. 615 14$aControl and Systems Theory. 615 24$aIndustrial and Production Engineering. 615 24$aIndustrial Chemistry/Chemical Engineering. 676 $a670.4275433 700 $aMhaskar$b Prashant$4aut$4http://id.loc.gov/vocabulary/relators/aut$01062897 702 $aGarg$b Abhinav$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aCorbett$b Brandon$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910484710803321 996 $aModeling and Control of Batch Processes$92847537 997 $aUNINA