|
|
|
|
| LEADER |
04314nmm a2200265 u 4500 |
| 001 |
EB000630862 |
| 003 |
EBX01000000000000000483944 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
140122 ||| eng |
| 020 |
|
|
|a 9781475718959
|
| 100 |
1 |
|
|a Narendra, Kumpati S.
|
| 245 |
0 |
0 |
|a Adaptive and Learning Systems
|h Elektronische Ressource
|b Theory and Applications
|c by Kumpati S. Narendra
|
| 250 |
|
|
|a 1st ed. 1986
|
| 260 |
|
|
|a New York, NY
|b Springer US
|c 1986, 1986
|
| 300 |
|
|
|a VIII, 418 p. 18 illus
|b online resource
|
| 505 |
0 |
|
|a Adaptive Control Theory -- Robust Adaptive Control -- Methods of Averaging for Adaptive Systems -- A Robust Indirect Adaptive Control Approach -- Global Stability of a Direct Adaptive Control Scheme With Respect to a Graph Topology -- Robust Discrete-Time Adaptive Control -- Identification and Adaptive Control of Linear Stochastic Systems -- Adaptive Control Applications -- On Practical Implementations of Adaptive Control -- Self Tuning and Adaptive Control of Chemical Processes -- Application of Multivariable Adaptive Control Schemes to Distillation Columns -- The Exact Pattern Recognition Adaptive Controller, a User-Oriented Commercial Success -- Self-Cohering a Large. Distorted Antenna for Microwave Imaging -- Identification of Robot Dynamics: An Application of Recursive Estimation -- Learning Systems -- Recent Developments in Learning Automata -- Learning Automata Models for Adaptive Flow Control in Packet-Switching Networks -- Application of Learning Automata to Image Data Compression -- Cooperativity in Networks of Pattern Recognizing Stochastic Learning Automata -- The Genetic Algorithm Approach: Why. How, and What Next? -- Knowledge Growth in an Artificial Animal -- Control of Flexible Space Structures -- Issues in Control Design for Large Space Structures -- Progress in Adaptive Control of Flexible Spacecraft Using Lattice Filters -- The Search for Appropriate Actuator Distribution Criteria in Large Space Structures Control -- Direct Model Reference Adaptive Control in Infinite-Dimensional Hilbert Space -- Robotics -- A Survey on Advances in the Theory of Computational Robotics -- Continuous Robot Motion Planning In Unknown Environment -- Impedance Control Applied to Automated Deburring -- The Potential Field Approach And Operational Space Formulation In Robot Control -- Mathematical Theoryof Learning with Applications to Robot Control -- Automatic Planning and Control of Robot Natural Motion Via Feedback -- Authors’ Index
|
| 653 |
|
|
|a Mathematical logic
|
| 653 |
|
|
|a Mathematical Logic and Foundations
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b SBA
|a Springer Book Archives -2004
|
| 028 |
5 |
0 |
|a 10.1007/978-1-4757-1895-9
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-1-4757-1895-9?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 511.3
|
| 520 |
|
|
|a This volume offers a glimpse of the status of research in adaptive and learning systems in 1985. In recent years these areas have spawned a multiplicity of ideas so rapidly that the average research worker or practicing engineer is overwhelmed by the flood of information. The Yale Workshop on Applications of Adaptive Systems Theory was organized in 1979 to provide a brief respite from this deluge, wherein critical issues may be examined in a calm and collegial environment. The fourth of the series having been held in May 1985, it has now become well established as a biennial forum for the lively exchange of ideas in the ever changing domain of adaptive systems. The scope of this book is broad and ranges from theoretical investigations to practical applications. It includes twenty eight papers by leaders in the field, selected from the Pro ceedings of the Fourth Yale Workshop and divided into five sections. I have provided a brief introduction to each section so that it can be read as a self-contained unit. The first section, devoted to adaptive control theory, suggests the intensity of activity in the field and reveals signs of convergence towards some common themes by workers with rather different moti vation. Preliminary results concerning the reduced order model problem are dramatically changing the way we view the field and bringing it closer to other areas such as robust linear control where major advances have been recently reported
|