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100   $a20250530d2025      u|         0
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aDynamic Models of Energy, Robotic, and Biological Systems $eSystems, Design, and Validation /$fby Jose de Jesus Rubio, Alejandro Zacarias, Jaime Pacheco
205   $a1st ed. 2025.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025.
215   $a1 online resource (XX, 182 p. 111 illus., 84 illus. in color.) 
311 08$a3-031-85437-3 
327   $a. Dynamic model of a wind turbine for the electric energy generation -- 2. An electricity generator based on the interaction of static and dynamic magnets -- 3. Dynamic model of an electric vehicle with energy recovery -- 4. Modeling and control of a fuel cell -- 5. Dynamic model with sensor and actuator for a transelevator -- 6. Dynamic model with sensor and actuator for an articulated robotic arm -- 7. Inverse dynamics model of a delta-type parallel robot -- 8. Acquisition system and approximation of brain signals -- 9. A method for online pattern recognition of abnormal eye movements -- 10. A method with neural networks for the classi.cation of fruits and vegeta-bles.
330   $aDynamic models are essential for understanding the system dynamics. It is of importance because one mistake in experiments could cause accidents or damages, while one mistake in the simulation of dynamic models could cause nothing. Each system has a different dynamic model; hence, this book presents the designs of 10 dynamic models which are mainly classified in two ways. The first kind of dynamic models are mainly obtained by the Euler Lagrange method and described by differential equations. The second kind of dynamic models are mainly obtained by the neural networks and described by difference equations. Topics and features: Contains the dynamic models of energy systems Derives dynamic models of energy systems by the Euler Lagrange method Includes the dynamic models of robotic systems Contains the dynamic models of biological systems Derives dynamic models of robotic systems by the Euler Lagrange method Obtains dynamic models of biological systems by neural networks This book is expected to be used primary by researchers and secondary by students and in the areas of control, robotics, energy, biological, mechanical, mechatronics, and computing systems. Jose de Jesus Rubio, Alejandro Zacarias, and Jaime Pacheco are full Professors affiliated with the ESIME Azcapotzalco, Instituto Politécnico Nacional, Sección de Estudios de Posgrado e Investigación, Ciudad de México, México.
606   $aComputer simulation
606   $aDynamics
606   $aBiological models
606   $aRobotics
606   $aComputer Modelling
606   $aDynamical Systems
606   $aBiological Models
606   $aRobotics
615  0$aComputer simulation.
615  0$aDynamics.
615  0$aBiological models.
615  0$aRobotics.
615 14$aComputer Modelling.
615 24$aDynamical Systems.
615 24$aBiological Models.
615 24$aRobotics.
676   $a003.3
700   $aRubio$b Jose de Jesus$4aut$4http://id.loc.gov/vocabulary/relators/aut$01821333
702   $aZacarias$b Alejandro$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aPacheco$b Jaime$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9911007467203321
996   $aDynamic Models of Energy, Robotic, and Biological Systems$94393349
997   $aUNINA