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_aTao, Gang _eauthor _9394 |
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| 245 | 1 | 0 |
_aAdaptive control design and analysis / _cGang Tao. |
| 264 | 1 |
_aHoboken, N.J. : _bWiley-Interscience, _c2004. |
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| 264 | 4 | _c©2003 | |
| 300 |
_a1 online resource (xx, 618 pages) : _billustrations. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 0 | _aAdaptive and learning systems for signal processing, communications, and control | |
| 504 | _aBIBINDX | ||
| 505 | 0 | _aMachine generated contents note: 1.1 Feedback in Control Systems -- 1.2 System Modeling -- 1.2.1 Continuous-Time Systems -- 1.2.2 Discrete-Time Systems -- 1.3 Feedback Control -- 1.4 Adaptive Control System Prototypes -- 1.5 Simple Adaptive Control Systems -- 1.5.1 Direct Adaptive Control -- 1.5.2 Indirect Adaptive Control -- 1.5.3 Discrete-Time Designs -- 1.5.4 Backstepping Nonlinear Design -- 1.5.5 Adaptive Control versus Fixed Control -- 1.5.6 Summary -- Problems -- 2.1 Dynamic System Models -- 2.1.1 Nonlinear Systems -- 2.1.2 Linear Systems -- 2.2 System Characterizations -- 2.3 Signal Measures -- 2.3.1 Vector and Matrix Norms -- 2.3.2 Signal Norms -- 2.4 Lyapunov Stability -- 2.4.1 Stability Definitions -- 2.4.2 Positive Definite Functions -- 2.4.3 Direct Method Lyapunov -- 2.4.4 Linear Systems -- 2.4.5 Lyapunov Indirect Method -- 2.5 Input-Output Stability -- 2.5.1 Lemma -- 2.5.2 Small-Gain Lemma -- 2.5.3 Operator Stability -- 2.5.4 Positive Real Strictly -- 2.6 Signal Convergence Lemmas -- 2.7 Discrete-Time Systems -- 2.7.1 System Modeling -- 2.7.2 Norms and Signal Spaces -- 2.7.3 Stability -- 2.8 Operator Norms -- 2.9 Pole Placement -- Problems -- 3.1 A Parametrized System Model -- 3.2 Linear Parametric Models -- 3.3 Normalized Gradient Algorithm -- 3.4 Normalized Least-Squares Algorithm -- 3.5 Parameter Convergence -- 3.5.1 Persistency of Excitation -- 3.5.2 Convergence of the Gradient Algorithm -- 3.5.3 Convergence of the Least-Squares Algorithm -- 3.6 Discrete-Time Algorithms -- 3.6.1 Linear Parametric Models -- 3.6.2 Normalized Gradient Algorithm -- 3.6.3 Normalized Least-Squares Algorithm -- 3.6.4 Parameter Convergence -- 3.7 Robustness of Adaptive Algorithms -- 3.7.1 Continuous-Time Algorithms -- 3.7.2 Discrete-Time Algorithms -- 3.8 Robust Adaptive Lans -- 3.8.1 Continuous-Time Algorithms -- 3.8.2 Discrete-Time Algorithms -- 3.8.3 Summary -- 3.9 Discussion -- Problems -- 4.1 Design for State Tracking -- 4.1.1 Design Example -- 4.1.2 Control System Structure -- 4.1.3 Adaptive Laws -- 4.1.4 Adaptive System Properties -- 4.2 Design for Output Tracking -- 4.2.1 Introductory Example -- 4.2.2 Control System Structure -- 4.2.3 Adaptive Laws -- 4.3 Disturbance Rejection -- 4.3.1 State Tracking -- 4.3.2 Output Tracking -- 4.4 Parametrization of State Feedback -- 4.4.1 Parametrization with Full-Order Observer -- 4.4.2 Parametrization with Reduced-Order Observer -- 4.5 Discrete-Time Adaptive Control -- 4.5.1 Design Example -- 4.5.2 Output Tracking Design -- 4.5.3 Disturbance Rejection -- 4.5.4 Parametrizations of State Feedback -- Problems -- 5.1 Control System Structure -- 5.2 Model Reference Control -- 5.3 Adaptive Control -- 5.3.1 Tracking Error Equation -- 5.3.2 Lyapunov Design for Relative Degree 1 -- 5.3.3 Alternative Design for Relative Degree 1 -- 5.3.4 Lyapunov Design for Arbitrary Relative Degrees -- 5.3.5 Gradient Design for Arbitrary Relative Degrees -- 5.3.6 Summary -- 5.4 Robustness of MRAC -- 5.4.1 Lyapunov Designs for Relative Degree 1 -- 5.4.2 Gradient Algorithms -- 5.5 Robust MRAC -- 5.5.1 Modeling Errors -- 5.5.2 Robustness of MRC -- 5.5.3 Robust Adaptive Laws -- 5.5.4 Robust Stability Analysis -- 5.5.5 Summary -- 5.6 Design for Unknown High Frequency Gain -- 5.6.1 Adaptive Control Designs Using Nussbaum Gain -- 5.6.2 An Adaptive Control System -- 5.7 Discussion -- Problems -- 6.1 Control System Structure -- 6.2 Model Reference Control -- 6.3 Adaptive Control Systems -- 6.3.1 Adaptive Control for Disturbance d(t)=0 -- 6.3.2 Robustness of MRAC with d(t) € L2 -- 6.3.3 Robust Adaptation for Bounded d(t) -- 6.4 Robustness of MRAC with L1+a Errors -- 6.4.1 Plant with Modeling Errors -- 6.4.2 Adaptive Control Scheme -- 6.4.3 Robustness Analysis -- 6.4.4 Discussion -- Problems -- 7.1 Model Reference Designs -- 7.1.1 Simple Adaptive Control Systems -- 7.1.2 General Design Procedure -- 7.2 Pole Placement Designs -- 7.2.1 Control System Structure -- 7.2.2 Pole Placement Control -- 7.2.3 Controller Parameter Adaptation -- 7.3 Discrete-Time Adaptive Control Systems -- 7.3.1 Model Reference Designs -- 7.3.2 Pole Placement Designs -- 7.4 Discussion -- Problems -- 8.1 Benchmark Example -- 8.2 Direct Adaptive Control Designs -- 8.2.1 State Feedback Design -- 8.2.2 Output Feedback Design -- 8.3 Indirect Adaptive Control Design -- 8.4 Direct-Indirect Adaptive Control Design -- 8.4.1 Direct Adaptive Control for Motor Dynamics -- 8.4.2 Indirect Adaptive Control for Load Dynamics -- 8.4.3 Simulation Results -- 8.5 Adaptive Backstepping Design -- Problems -- 9.1 Adaptive State Feedback Control -- 9.1.1 Design for State Tracking -- 9.1.2 Design Based on LDU Parametrization -- 9.1.3 System Identification -- 9.2 Model Reference Adaptive Control -- 9.2.1 Description of Multivariable Systems -- 9.2.2 Plant and Controller Parametrizations -- 9.2.3 Robust Model Reference Control -- 9.2.4 Error Model -- 9.2.5 Adaptive Laws -- 9.2.6 Stability and Robustness Analysis -- 9.2.7 MRAC Using Right Interactor Matrices -- 9.2.8 Continuous-Time Lyapunov Designs -- 9.2.9 MRAC Designs for Input and Output Delays -- 9.2.10 Adaptation and High Frequency Gain Matrix -- 9.2.11 Designs Based on Decompositions of Kp -- 9.3 Adaptive Backstepping Control -- 9.3.1 Plant Parametrization -- 9.3.2 State Observer -- 9.3.3 Design Procedure for Bm Nonsingular -- 9.3.4 Design Based on SDU Decomposition of Bm -- 9.3.5 Design Procedure for Bm Singular -- 9.4 Adaptive Control of Robotic Systems -- 9.4.1 Robotic System Modeling -- 9.4.2 Illustrative Example -- 9.4.3 Design for Parameter Variations -- 9.4.4 Design for Unmodeled Dynamics -- 9.5 Discussion -- Problems -- 10.1 Actuator Nonlinearity Compensation -- 10.1.1 Actuator Nonlinearities -- 10.1.2 Parametrized Nonlinearity Inverses -- 10.2 State Feedback Inverse Control -- 10.3 Output Feedback Inverse Control -- 10.4 Designs for Multivariable Systems -- 10.5 Designs for Unknown Linear Dynamics -- 10.5.1 Designs for SISO Plants -- 10.5.2 Designs for MIMO Plants -- 10.6 Designs for Nonlinear Dynamics -- 10.6.1 Design for Feedback Linearizable Systems -- 10.6.2 Design for Parametric-Strict-Feedback Systems -- 10.6.3 Design for Output-Feedback Systems -- 10.7 Discussion -- Problems. | |
| 520 | 8 |
_aAnnotation _b"Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory." "As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike."--BOOK JACKET. Title Summary field provided by Blackwell North America, Inc. All Rights Reserved. |
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| 650 | 0 |
_aAdaptive control systems _9396 |
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| 650 | 6 | _aSystèmes adaptatifs. | |
| 650 | 7 |
_aAdaptive control systems. _2fast _0(OCoLC)fst00796490 |
|
| 650 | 0 | 7 |
_aAdaptivregelung. _2swd |
| 653 |
_aControl systems technology _aControl process measurements. |
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| 655 | 7 |
_aElectronic books. _2local |
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| 710 | 2 | _aJohn Wiley & Sons. | |
| 776 | 0 | 8 |
_iPrint version: _aTao, Gang. _tAdaptive control design and analysis. _dHoboken, N.J. : Wiley-Interscience, ©2003 _z0471274526 _w(DLC) 2003041152 |
| 856 | 4 | 0 |
_3Wiley Online Library _zOnline access link to the resource _uhttps://doi.org/10.1002/0471459100 |
| 942 |
_2lcc _cEBK |
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