000 | 04152nam a22006015i 4500 | ||
---|---|---|---|
001 | 978-3-319-53312-4 | ||
003 | DE-He213 | ||
005 | 20220801222725.0 | ||
007 | cr nn 008mamaa | ||
008 | 170207s2017 sz | s |||| 0|eng d | ||
020 |
_a9783319533124 _9978-3-319-53312-4 |
||
024 | 7 |
_a10.1007/978-3-319-53312-4 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aTEC009000 _2bisacsh |
|
072 | 7 |
_aUYQ _2thema |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aGarcia-Hernandez, Ramon. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _963009 |
|
245 | 1 | 0 |
_aDecentralized Neural Control: Application to Robotics _h[electronic resource] / _cby Ramon Garcia-Hernandez, Michel Lopez-Franco, Edgar N. Sanchez, Alma y. Alanis, Jose A. Ruz-Hernandez. |
250 | _a1st ed. 2017. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017. |
|
300 |
_aXV, 111 p. 54 illus., 3 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aStudies in Systems, Decision and Control, _x2198-4190 ; _v96 |
|
505 | 0 | _aIntroduction -- Foundations -- Decentralized Neural Block Control -- Decentralized Neural Backstepping Control -- Decentralized Inverse Optimal Control for Stabilization: a CLF Approach -- Decentralized Inverse Optimal Control for Trajectory Tracking -- Robotics Application -- Conclusions. | |
520 | _aThis book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work. . | ||
650 | 0 |
_aComputational intelligence. _97716 |
|
650 | 0 |
_aControl engineering. _931970 |
|
650 | 0 |
_aRobotics. _92393 |
|
650 | 0 |
_aAutomation. _92392 |
|
650 | 1 | 4 |
_aComputational Intelligence. _97716 |
650 | 2 | 4 |
_aControl and Systems Theory. _931972 |
650 | 2 | 4 |
_aControl, Robotics, Automation. _931971 |
700 | 1 |
_aLopez-Franco, Michel. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _963010 |
|
700 | 1 |
_aSanchez, Edgar N. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _963011 |
|
700 | 1 |
_aAlanis, Alma y. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _963012 |
|
700 | 1 |
_aRuz-Hernandez, Jose A. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _963013 |
|
710 | 2 |
_aSpringerLink (Online service) _963014 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319533117 |
776 | 0 | 8 |
_iPrinted edition: _z9783319533131 |
776 | 0 | 8 |
_iPrinted edition: _z9783319851235 |
830 | 0 |
_aStudies in Systems, Decision and Control, _x2198-4190 ; _v96 _963015 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-53312-4 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c81086 _d81086 |