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035   $a(DE-He213)978-3-030-18068-3
035   $a(PPN)243770006
035   $a(EXLCZ)994100000007992416
100   $a20190416d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAdaptive and Intelligent Control of Microbial Fuel Cells /$fby Ravi Patel, Dipankar Deb, Rajeeb Dey, Valentina E. Balas
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (135 pages)
225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v161
311   $a3-030-18067-0 
327   $aIntroduction -- Mathematical Modelling -- Model Analysis of Single Population Single Chamber MFC -- Robust Control design of SPSC Microbial Fuel Cell with norm bounded uncertainty -- Introduction to Adaptive Control. .
330   $aThis book addresses a range of solutions and effective control techniques for Microbial Fuel Cells (MFCs), intended as a response to the increased energy consumption and wastewater production stemming from globalization. It describes the fundamentals of MFCs and control-oriented mathematical models, and provides detailed information on uncertain parameters. Various control techniques like robust control with LMI, adaptive backstepping control, and exact linearization control are developed for different mathematical models. In turn, the book elaborates on the basics of adaptive control, presenting several methods in detail. It also demonstrates how MFCs can be developed at the laboratory level, equipping readers to develop their own MFCs for experimental purposes. In closing, it develops a transfer function model for MFCs by combining a system identification technique and model reference adaptive control techniques. By addressing one of the most promising sources of clean and renewable energy, this book provides a viable solution for meeting the world?s increasing energy demands.
410  0$aIntelligent Systems Reference Library,$x1868-4394 ;$v161
606   $aComputational intelligence
606   $aRenewable energy resources
606   $aElectrochemistry
606   $aControl engineering
606   $aArtificial intelligence
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aRenewable and Green Energy$3https://scigraph.springernature.com/ontologies/product-market-codes/111000
606   $aElectrochemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/C21010
606   $aControl and Systems Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/T19010
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
615  0$aComputational intelligence.
615  0$aRenewable energy resources.
615  0$aElectrochemistry.
615  0$aControl engineering.
615  0$aArtificial intelligence.
615 14$aComputational Intelligence.
615 24$aRenewable and Green Energy.
615 24$aElectrochemistry.
615 24$aControl and Systems Theory.
615 24$aArtificial Intelligence.
676   $a621.312429
700   $aPatel$b Ravi$4aut$4http://id.loc.gov/vocabulary/relators/aut$01229608
702   $aDeb$b Dipankar$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aDey$b Rajeeb$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aBalas$b Valentina Emilia$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910483118203321
996   $aAdaptive and Intelligent Control of Microbial Fuel Cells$92854189
997   $aUNINA