LEADER 05154nam 2200661Ia 450 001 9910782391203321 005 20230607222126.0 010 $a1-281-95174-9 010 $a9786611951740 010 $a981-281-022-6 035 $a(CKB)1000000000538054 035 $a(EBL)1679471 035 $a(OCoLC)815754721 035 $a(SSID)ssj0000148138 035 $a(PQKBManifestationID)11157471 035 $a(PQKBTitleCode)TC0000148138 035 $a(PQKBWorkID)10018593 035 $a(PQKB)11107038 035 $a(MiAaPQ)EBC1679471 035 $a(WSP)00004636 035 $a(Au-PeEL)EBL1679471 035 $a(CaPaEBR)ebr10255441 035 $a(CaONFJC)MIL195174 035 $a(EXLCZ)991000000000538054 100 $a20010612d2001 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aEntropy in control engineering$b[electronic resource] /$fGeorge N. Saridis 210 $aSingapore ;$aRiver Edge, NJ $cWorld Scientific$dc2001 215 $a1 online resource (148 p.) 225 1 $aSeries in intelligent control and intelligent automation ;$vv. 12 300 $aDescription based upon print version of record. 311 $a981-02-4551-3 320 $aIncludes bibliographical references and index. 327 $aContents ; Table Of Figures ; Preface ; Chapter 1 Entropy, Control, Chaos; 1.1 Introduction: ; 1.2 Global Entropy ; 1.2.1 Review Of Entropy Concepts ; 1.2.2 Entropy And Thermodynamics ; 1.2.3 Entropy And Information Theory ; 1.2.4 e-Entropy; 1.2.5 Jaynes' Principle Of Maximum Entropy 327 $a1.2.6 The Principle Of Increasing Precision Decreasing Intelligence 1.2.7 Entropy And The Environment ; 1.3 Uncertainty And The Control Problem ; 1.4 The Human Interaction ; 1.5 Automatic Control Systems ; 1.6 Entropy Formulation Of Control ; 1.7 Conclusions ; 1.8 References 327 $aChapter 2 Stochastic Optimal Estimation And Control 2.1 Introduction ; 2.2 The Deterministic Optimal Control ; 2.3 The Stochastic Optimal Control Problem ; 2.4 The Stochastic Suboptimal Control Problem ; 2.5 Discrete-Time Formulation Of The Stochastic Optimal Control Problem 327 $a2.6 Maximum Entropy Formulation Of State Estimation: Continuous-Time 2.7 Maximum Entropy Formulation Of State Estimation: Discrete-Time ; 2.8 The Cost Of Active Feedback (Dual) Control Problem ; 2.9 Stochastic Optimal (Dual) Estimation And Control 327 $a2.10 Stochastic Suboptimal Control Revisited 2.11 Stochastic Optimal Adaptive Control ; 2.11.1 Example: The Dual-Optimal And Adaptive Control ; 2.12 The LQG Optimal Control And The Kalman-Bucy Filter; 2.13 Upper Bound Of The Equivocation H[o/u*]; 2.13.1 Example: The Upper Bound Of Equivocation ; 2.14 Conclusions ; 2.15 References 327 $aChapter 3 Review Of Intelligent Control Systems 330 $a This book attempts to couple control engineering with modern developments in science, through the concept of entropy. Such disciplines as intelligent machines, economics, manufacturing, environmental systems, waste etc. can be favorably affected and their performance can be improved or their catastrophic effects minimized. Entropy is used as the unifying measure of the various, seemingly disjoint, disciplines to represent the cost of producing work that improves the standard of living, both in engineering and in science. Modeling is done through probabilistic methods, thus establishing the ir 410 0$aSeries in intelligent control and intelligent automation ;$vv. 12. 606 $aEntropy (Information theory) 606 $aIntelligent control systems 615 0$aEntropy (Information theory) 615 0$aIntelligent control systems. 676 $a629.8 700 $aSaridis$b George N.$f1931-$058805 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910782391203321 996 $aEntropy in control engineering$92645099 997 $aUNINA