05154nam 2200661Ia 450 991078239120332120230607222126.01-281-95174-99786611951740981-281-022-6(CKB)1000000000538054(EBL)1679471(OCoLC)815754721(SSID)ssj0000148138(PQKBManifestationID)11157471(PQKBTitleCode)TC0000148138(PQKBWorkID)10018593(PQKB)11107038(MiAaPQ)EBC1679471(WSP)00004636(Au-PeEL)EBL1679471(CaPaEBR)ebr10255441(CaONFJC)MIL195174(EXLCZ)99100000000053805420010612d2001 uy 0engur|n|---|||||txtccrEntropy in control engineering[electronic resource] /George N. SaridisSingapore ;River Edge, NJ World Scientificc20011 online resource (148 p.)Series in intelligent control and intelligent automation ;v. 12Description based upon print version of record.981-02-4551-3 Includes bibliographical references and index.Contents ; 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 Entropy1.2.6 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 ReferencesChapter 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 Problem2.6 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 Control2.10 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 ReferencesChapter 3 Review Of Intelligent Control Systems 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 irSeries in intelligent control and intelligent automation ;v. 12.Entropy (Information theory)Intelligent control systemsEntropy (Information theory)Intelligent control systems.629.8Saridis George N.1931-58805MiAaPQMiAaPQMiAaPQBOOK9910782391203321Entropy in control engineering2645099UNINA