Frontiers in Adaptive Control Part 2 ppt

Frontiers in Adaptive Control Part 2 ppt

Frontiers in Adaptive Control Part 2 ppt

... indexed by { } 0,1, 2, , 1kN∈−K , as follows: • 22 02 : k HM χ ∈ • 22 12 : k HM χ ∉ Frontiers in Adaptive Control 34 2. Frequency Dependent Model Validation The main objective of the ... (1994). Modeling of dynamic systems, Prentice-Hall, Inc., ISBN 0-13- 597097-0, NJ Frontiers in Adaptive Control 22 Recursive Least-Squares (RLS) In adaptive controll...

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Frontiers in Adaptive Control Part 1 pdf

Frontiers in Adaptive Control Part 1 pdf

... The adaptation gain in eq. (23 ) is determined as: The control gains and in eq. (14) are set to be: The weighing matrix in the composite adaptive control (25 ) is determined as: mass ... tracking control, the Lyapunov function (20 ) is considered again. The time- derivative of (20 ) is derived as (21 ). Since the adaptive control law is determined by (25 ),...

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Frontiers in Adaptive Control Part 3 potx

Frontiers in Adaptive Control Part 3 potx

... with 2 10 σ − = . The reference input r is a train of sinusoids up to frequency 20 0 rad/sec. Finally, the plant G to be controlled is sixth order, given by 6 22 22 10 ( 1000) ( 0.0 02 1000 ... space , Frontiers in Adaptive Control 62 4. Particle Filters in Robotic Control and Planning The monograph by Thrun et al. (20 05) gives a comprehensive treatment of the eme...

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Frontiers in Adaptive Control Part 5 potx

Frontiers in Adaptive Control Part 5 potx

... positive definite matrix. Then, ] )( )([ 2 1 min 2 2 min K ε sKεsKss λ λ −≤+− TT . (A.1) Proof: ] )( )([ 2 1 ] )( )([ 2 1 ] )( )([ 2 1 ])([ min 2 2 min min 2 2 min 2 min min min K ε sK K ε sK K ε sK sεsKεsKss λ λ λ λ λ λ λ −−≤ −− −−= +−≤+− TT ... ϑ ϑ ϑϑ ϑϑ ϑ ϑ ⎡⎤ ⎢⎥ ⎢⎥ ⎢⎥ ⎢⎥ ⎢⎥ ⎢⎥ ⎢⎥ ⎢⎥ ⎣⎦ ++∗∗ =+∗ −− ⎡ ⎤ ⎢ ⎥ = ⎢ ⎥ ⎢ ⎥ ⎣ ⎦ && & 12 23 3 22 3 44 4...

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Frontiers in Adaptive Control Part 7 pot

Frontiers in Adaptive Control Part 7 pot

... matrix is given in Section 6 .2. Frontiers in Adaptive Control 144 Ruan X., Ding M., Gong D., & Qiao J. (20 07). On-line adaptive control for inverted pendulum balancing based on feedback-error-learning, ... non-linear systems containing time- varying uncertainties with unknown bounds. International Journal of Control, Vol. 74, No. 3, pp. 25 2 -26 4. Huang A. C., &a...

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Frontiers in Adaptive Control Part 8 doc

Frontiers in Adaptive Control Part 8 doc

... type according to both the human interpretation and machine interpretation Frontiers in Adaptive Control 1 82 Furthermore, the data shows an increase in pending tracks in the smuggling scenarios ... 20 07, 27 6 -28 5, 978-3-540-7 321 5-0, Beijing, China, July 22 -27 , Springer Berlin, Heidelberg De Greef, T.E.; Arciszewski, H.F.R.; Lindenberg, J. & Van Delft, J.H. (...

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Frontiers in Adaptive Control Part 9 docx

Frontiers in Adaptive Control Part 9 docx

... continuous-time nonlinear systems. In American Control Conference, 20 02. Proceedings of the 20 02, volume 1, pages 394-399vol. 1, 8-10 May 20 02. [6] M. A. Golberg. The derivative of a determinant. ... that . 2. This can be shown by noting from (17) that . Since (.) and e are bounded signals and , the integral term exists and it is finite. Frontiers in Adaptive Contro...

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Frontiers in Adaptive Control Part 11 docx

Frontiers in Adaptive Control Part 11 docx

... 20 00a). Frontiers in Adaptive Control 26 2 0 100 20 0 300 400 0 0.05 0.1 0.15 0 .2 0 .25 0.3 0.35 0.4 0.45 0.5 Step Response Time ( sec ) Amplitude -100 -50 0 50 Magnitude (dB) 10 -3 10 -2 10 -1 10 0 -360 -27 0 -180 -90 0 Phase ... minimize is continuous (Pintér, 1996). Taking all these into account, and considering that the set of functions to minimize in this case is...

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Frontiers in Adaptive Control Part 12 pdf

Frontiers in Adaptive Control Part 12 pdf

... J. D. Bronzino, B. D. Bronzino (Eds)CRC Press, ISBN 0849 321 220 Bernstein, D. (20 02) . Feedback control: an invisible thread in the history of technology. IEEE Ctrl Syst Mag, 22 (2) , pp 53-68 ... L L M L L L M L MOMM L L L LL M L L ++++ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ = ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎣ ⎡ ++ ++ ++ ++ + ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢ ⎢ ⎣ ⎡ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎣ ⎡ = ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢...

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Frontiers in Adaptive Control Part 14 pot

Frontiers in Adaptive Control Part 14 pot

... wave-pipelining scheme works properly while minimizing the response time in the adaptive control loop. Figure 7. Wave-pipelining scheme for the control signal 3.3 Adaptive Fetching Point Control ... 422 -433, Sep-Oct 20 05. [14] G. De Micheli, Designing Robust Systems with Uncertain Information, Invited talk, Asia- Pacific Design Automation Conference, 20 03. [15] Fro...

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