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000823710 019__ $$a1004758378$$a1006495868$$a1012444519$$a1021274180
000823710 020__ $$a9789811052637$$q(electronic book)
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000823710 0247_ $$a10.1007/978-981-10-5263-7$$2doi
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000823710 050_4 $$aTJ217.5$$b.L585 2018eb
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000823710 1001_ $$aLiu, Jinkun,$$d1965-$$eauthor.
000823710 24510 $$aIntelligent control design and MATLAB simulation /$$cJinkun Liu.
000823710 264_1 $$aSingapore :$$bSpringer,$$c[2018]
000823710 264_4 $$c©2018
000823710 300__ $$a1 online resource (xv, 290 pages) :$$billustrations
000823710 336__ $$atext$$btxt$$2rdacontent
000823710 337__ $$acomputer$$bc$$2rdamedia
000823710 338__ $$aonline resource$$bcr$$2rdacarrier
000823710 347__ $$atext file$$bPDF$$2rda
000823710 504__ $$aIncludes bibliographical references.
000823710 5050_ $$aPreface; Contents; About the Author; Abstract; 1 Introduction to Intelligent Control; 1.1 Expert Control; 1.2 Fuzzy Logic Control; 1.3 Neural Network and Control; 1.4 Intelligent Search Algorithm; References; 2 Expert PID Control; 2.1 Expert PID Control; 2.2 Simulation Example; Reference; 3 Foundation of Fuzzy Mathematics; 3.1 Characteristic Function and Membership Function; 3.2 Fuzzy Set Expression; 3.3 Calculation Method of Fuzzy Set; 3.3.1 Basic Calculation Method of Fuzzy Set; 3.3.2 Fuzzy Operator; 3.3.3 Typical Membership Function; 3.3.4 Design of Fuzzy System.
000823710 5058_ $$a3.4 Fuzzy Matrix Calculation3.4.1 Fuzzy Matrix; 3.4.2 Fuzzy Matrix Calculation; 3.4.3 Compound of Fuzzy Matrix; 3.5 Fuzzy Inference; 3.6 Fuzzy Equation; Reference; 4 Fuzzy Logic Control; 4.1 Design of Fuzzy Logic Controller; 4.2 An Example for a Fuzzy Logic Controller Design; 4.3 Fuzzy Logic Control for Washing Machine; 4.4 Fuzzy PI Control; 4.4.1 PI Tuning Controller with Fuzzy Logic; 4.4.2 Simulation Example; References; 5 Fuzzy T-S Modeling and Control; 5.1 Fuzzy T-S Model; 5.2 Fuzzy T-S Modeling and Control Based on LMI; 5.2.1 Controller Design of T-S Fuzzy Model Based on LMI.
000823710 5058_ $$a5.2.2 LMI Design and Analysis5.2.3 Transformation of LMI; 5.2.4 LMI Design Example; 5.3 Fuzzy T-S Modeling and Control Based on LMI for Inverted Pendulum; 5.3.1 System Description; 5.3.2 Simulation Based on Two Fuzzy Rules Design; 5.3.3 Simulation Based on Four Fuzzy Rules Design; 5.4 Simulation Example of YALMIP Toolbox; References; 6 Adaptive Fuzzy Control; 6.1 Adaptive Fuzzy Control; 6.2 Fuzzy Approximation; 6.2.1 Fuzzy System Design; 6.2.2 Fuzzy System Approximation; 6.2.3 Simulation Example; 6.2.3.1 One Dimension Function Approximation; 6.2.3.2 Two Dimension Function Approximation.
000823710 5058_ $$a6.3 Adaptive Fuzzy Controller Design6.3.1 Problem Description; 6.3.2 Fuzzy Approximation; 6.3.3 Adaptive Fuzzy Control Design and Analysis; 6.3.4 Simulation Example; 6.4 Adaptive Fuzzy Control Based on Fuzzy System Compensator; 6.4.1 System Description; 6.4.2 Adaptive Fuzzy Control Design and Analysis; 6.4.3 Only Consider Friction; 6.4.4 Simulation Example; References; 7 Neural Networks; 7.1 Introduction; 7.2 Single Neural Network; 7.3 BP Neural Network Design and Simulation; 7.3.1 BP Network Structure; 7.3.2 Approximation of BP Neural Network; 7.3.3 Simulation Example.
000823710 5058_ $$a7.4 RBF Neural Network Design and Simulation7.4.1 RBF Algorithm; 7.4.2 RBF Design Example with MATLAB Simulation; 7.4.2.1 For Structure 1-5-1 RBF Neural Network; 7.4.2.2 For Structure 2-5-1 RBF Neural Network; 7.5 RBF Neural Network Approximation Based on Gradient Descent Method; 7.5.1 RBF Neural Network Approximation; 7.5.2 Simulation Example; 7.6 Effects of Analysis on RBF Approximation; 7.6.1 Effects of Gaussian Function Parameters on RBF Approximation; 7.6.2 Effects of Hidden Nets Number on RBF Approximation; 7.7 RBF Neural Network Training for System Modeling.
000823710 506__ $$aAccess limited to authorized users.
000823710 520__ $$aThis book offers a comprehensive introduction to intelligent control system design, using MATLAB simulation to verify typical intelligent controller designs. It also uses real-world case studies that present the results of intelligent controller implementations to illustrate the successful application of the theory. Addressing the need for systematic design approaches to intelligent control system design using neural network and fuzzy-based techniques, the book introduces the concrete design method and MATLAB simulation of intelligent control strategies; offers a catalog of implementable intelligent control design methods for engineering applications; provides advanced intelligent controller design methods and their stability analysis methods; and presents a sample simulation and Matlab program for each intelligent control algorithm. The main topics addressed are expert control, fuzzy logic control, adaptive fuzzy control, neural network control, adaptive neural contro l and intelligent optimization algorithms, providing several engineering application examples for each method.
000823710 588__ $$aDescription based on print version record.
000823710 63000 $$aMATLAB.
000823710 650_0 $$aIntelligent control systems.
000823710 77608 $$iPrint version:$$aLiu, Jinkun, 1965-$$tIntelligent control design and MATLAB simulation.$$dSingapore : Springer, 2018$$z981105262X
000823710 852__ $$bebk
000823710 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-10-5263-7$$zOnline Access$$91397441.1
000823710 909CO $$ooai:library.usi.edu:823710$$pGLOBAL_SET
000823710 980__ $$aEBOOK
000823710 980__ $$aBIB
000823710 982__ $$aEbook
000823710 983__ $$aOnline
000823710 994__ $$a92$$bISE