LEADER 04151nam 2200589 a 450 001 9911006753303321 005 20200520144314.0 010 $a1-62198-561-X 010 $a1-84919-608-7 010 $a1-299-10439-8 035 $a(CKB)2550000001004172 035 $a(EBL)1117245 035 $a(OCoLC)854970326 035 $a(SSID)ssj0000906779 035 $a(PQKBManifestationID)12376770 035 $a(PQKBTitleCode)TC0000906779 035 $a(PQKBWorkID)10855782 035 $a(PQKB)11045409 035 $a(MiAaPQ)EBC1117245 035 $a(EXLCZ)992550000001004172 100 $a20130212d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDistributed control and filtering for industrial systems /$fMagdi S. Mahmoud 210 $aLondon $cInstitution of Engineering and Technology$d2013 215 $a1 online resource (484 p.) 225 0$aIET control engineering series ;$v88 300 $aDescription based upon print version of record. 311 $a1-84919-607-9 320 $aIncludes bibliographical references and index. 327 $aContents; Preface; Acknowledgments; Notations and symbols; List of acronyms; 1. Introduction; 1.1 Introduction; 1.2 Control architectures; 1.3 Related design problems and issues; 1.4 Information flow; 1.5 Performance evaluation; 1.6 Advantages of distributed control systems; 1.7 Outline of the book; 1.8 Notes; 2. Distributed model predictive control; 2.1 Overview; 2.2 Dissipativity-based approach; 2.3 Constrained model predictive control; 2.4 A cooperative game approach; 2.5 Feasible cooperation model predictive control; 2.6 Application to power plant control 327 $a2.7 Application to quadruple-tank process2.8 Application to automatic generation control; 2.9 Notes; 3. Distributed linear quadratic control; 3.1 Introduction; 3.2 Identical decoupled dynamical systems; 3.3 Distributed semistable LQR control; 3.4 Distributed control of nonnegative systems; 3.5 Distributed control of power load frequency; 3.6 Notes; 4. Distributed observer-based control; 4.1 Observer-based control; 4.2 Approximate distributed feedback control; 4.3 Application to chemical reactors; 4.4 Notes; 5. Distributed consensus control; 5.1 Consensus of multiagent systems 327 $a5.2 Consensus control for time-delay systems5.3 Robust consensus of multiagent systems; 5.4 Notes; 6. Distributed estimation; 6.1 Introduction; 6.2 Problem formulation; 6.3 Convergence of the centralized estimation error; 6.4 Minimum variance estimation design; 6.5 Asynchronous multirate multismart sensors; 6.6 Distributed nonlinear estimation; 6.7 Notes; 7. Distributed Kalman filtering; 7.1 Introduction; 7.2 Self-tuning Kalman filtering; 7.3 Kalman filtering with intermittent communications; 7.4 Notes; 8. Experimental setups; 8.1 Introduction; 8.2 Overview of related work 327 $a8.3 Simulation environments8.4 Simulation examples; 8.5 Experimental setup; 8.6 Multiagent modeling approach; 8.7 Networked control system evaluation; 8.8 CAN and Switched Ethernet networks; 8.9 Design consideration; 8.10 Networked and distributed control architectures; 8.11 Notes; 9. Appendix; 9.1 Notations; 9.2 Elements of graph theory; 9.3 Minimum mean square estimate; 9.4 Stability notions; 9.5 Basic inequalities; 9.6 Linear matrix inequalities; 9.7 Some formulas on matrix inverses; References; Index 330 $aDistributed Control and Filtering for Industrial Systems provides an introduction to the control and filtering algorithms devised for distributed environments, with a particular emphasis on industrial applications. 606 $aAutomatic control 606 $aIndustrial engineering 615 0$aAutomatic control. 615 0$aIndustrial engineering. 676 $a629.8 700 $aMahmoud$b Magdi S$020659 712 02$aInstitution of Engineering and Technology. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911006753303321 996 $aDistributed control and filtering for industrial systems$94392030 997 $aUNINA