FUZZY LOGIC – ALGORITHMS, TECHNIQUES AND IMPLEMENTATIONS ppt

FUZZY LOGIC – ALGORITHMS, TECHNIQUES AND IMPLEMENTATIONS ppt

FUZZY LOGIC – ALGORITHMS, TECHNIQUES AND IMPLEMENTATIONS ppt

... Judgment: Fuzzy Set Model and Data Analysis  From Fuzzy Datalog to Multivalued Knowledge-Base  Resolution Principle and Fuzzy Logic  Standard Fuzzy Sets and Some Many-Valued Logics  ... 0 0 100 100 Fuzzy Logic – Algorithms, Techniques and Implementations 24 Sherif,M.,& Hovland,C,I. (1961). Social judgment: Assimilation and contrast ef...

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FUZZY LOGIC – ALGORITHMS, TECHNIQUES AND IMPLEMENTATIONS potx

FUZZY LOGIC – ALGORITHMS, TECHNIQUES AND IMPLEMENTATIONS potx

... (1992). Multiobjective fuzzy linear regression analysis for fuzzy input-output data. Fuzzy Sets and Systems, 47, 17 3–1 81. Fuzzy Logic – Algorithms, Techniques and Implementations 26 In ... Resolution Principle and Fuzzy Logic 55 Hashim Habiballa Chapter 4 Standard Fuzzy Sets and some Many-Valued Logics 75 Jorma K. Mattila Chapter 5 Parametric Ty...

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Essentials of Control Techniques and Theory_1 pptx

Essentials of Control Techniques and Theory_1 pptx

... variables. Figure 1.3 Ball -and- plate integrator. 91239.indb 7 10/12/09 1:40:43 PM 8 ◾ Essentials of Control Techniques and Theory Computer simulation and discrete time control go hand in hand together. At ... 81 7.5 Eigenfunctions and Gain 81 7.6 A Surfeit of Feedback 83 7.7 Poles and Polynomials 85 7.8 Complex Manipulations 87 7.9 Decibels and Octaves 88 7.10 Frequency Plots...

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Essentials of Control Techniques and Theory_10 pptx

Essentials of Control Techniques and Theory_10 pptx

... ◾ Essentials of Control Techniques and Theory and added a controller with state z, where  zKzLyMv=++ We apply signals from the controller dynamics, the command input and the system output ...  xax=− has a pole at –a, and is stable no matter how large a is made. On the other hand, the discrete time approximation to this system βxax=− also has a pole at –a, but if a is incr...

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Essentials of Control Techniques and Theory_13 pptx

Essentials of Control Techniques and Theory_13 pptx

... 45 Matrices and eigenvectors, 10 3–1 04 Matrix state equations, 2 3–2 4 Maximum Principle, 30 9–3 10 M-circles and Nyquist plot, 15 1–1 52 Microsoft version QBasic, 12 Microswitches, 42 MIMO, see Multi-input and ... equations, 14 0–1 44 and time functions, 271 Leakage rate, 1 0–1 1 Limit switches, 42 91239.indb 320 10/12/09 1:49:03 PM 312 ◾ Essentials of Control Techniqu...

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Essentials of Control Techniques and Theory_3 pptx

Essentials of Control Techniques and Theory_3 pptx

... Control Techniques and Theory where v n is a command input. As in the continuous case, we can substitute the expression for u back into the system equations to get xMxNFy Gv nnnn+ =+ + 1 () and ... simply try x n = k n and the equation becomes kkk nnn++ ++= 21 50, so we have ()kkk n2 56 0++ = and once more we find ourselves solving a quadratic to find k = –2 or k = –3 ....

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Essentials of Control Techniques and Theory_4 pptx

Essentials of Control Techniques and Theory_4 pptx

... can equate coefficients to obtain   A u x v y = ∂ ∂ = ∂ ∂ and   B v x u y = ∂ ∂ = ∂ ∂ − .   (10.5) Leave out A and B and these are the Cauchy–Riemann equations. e main interest of such mappings ... error is now (command-x), so we can demand an angle of tilt tiltdem = c*(command-x)-d*vest; which we then constrain with if(tiltdem>.1){tiltdem=.1;} if(tiltdem< 1){tiltdem= 1;} and we...

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Essentials of Control Techniques and Theory_7 pptx

Essentials of Control Techniques and Theory_7 pptx

... g(t). u 1 u 2 u 2 u 1 u 3 u 3 τ 1 τ 2 τ 2 τ 1 τ 3 τ 2 τ 1 τ 3 τ 3 τ 1 τ 2 τ 3 t t t t (t – τ 1 ) (t – τ 2 ) (t – τ 3 ) u 1 g(t – τ 1 ) u 2 g(t – τ 2 ) u 3 g(t – τ 3 ) Figure 15.4 Superposition of impulse responses. 91239.indb 208 10/12/09 1:45:44 PM 224 ◾ Essentials of Control Techniques ... dt st (–) – −∞ ∞ ∫ 91239.indb 205 10/12/09 1:45:39 PM 218 ◾ Essenti...

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Essentials of Control Techniques and Theory_11 pptx

Essentials of Control Techniques and Theory_11 pptx

... 30 0–3 05 E E and I pickoff variable transformer, 44 Eigenfunctions and continuous time equations, 10 4–1 05 eigenvalues and eigenvectors, 21 8–2 20 and gain, 8 1–8 3 linear system for, 83 matrices and ... 45 Matrices and eigenvectors, 10 3–1 04 Matrix state equations, 2 3–2 4 Maximum Principle, 30 9–3 10 M-circles and Nyquist plot, 15 1–1 52 Microsoft version QBa...

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CT SCANNING – TECHNIQUES AND APPLICATIONS ppt

CT SCANNING – TECHNIQUES AND APPLICATIONS ppt

... in any direction and the optimal direction is dependent on the patient’s vascular anatomy and the individual findings and therefore should be done individually and not in a standardized way. ... CT Scanning – Techniques and Applications 40 Figure 2 is a schematic picture of an optical CT scanner using a broad, collimated beam and a charge coupled detector (CCD) (Krst...

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