caa a22 4500 475834135 CHVBK 20180406123849.0 cr unu---uuuuu 170329e20000701xx s 000 0 eng 10.1007/s005210070022 doi (NATIONALLICENCE)springer-10.1007/s005210070022 Delgado A. Electrical and Electronics Engineering Department, National University of Colombia, Bogota, Colombia, CO aut Control of Nonlinear Systems Using a Self-Organising Neural Network [Elektronische Daten] [A. Delgado] Two applications of Self Organising Map (SOM) networks in the context of nonlinear control are introduced, one in approximate feedback linearisation and the second in optimal control. It is shown that a modified SOM can be used to approximately Input/Output (I/O) linearise and to control nonlinear systems using a combination of the SOM learning algorithm, and a biologically inspired optimisation algorithm known as chemotaxis. A proof to guarantee the stability of the closed loop during the training of the network and the operation of the whole system is included. The results are illustrated with simulations of a single link manipulator.: Springer-Verlag London Limited, 2000 Keywords:Chemotaxis nationallicence Input/output linearisation nationallicence Linear splines nationallicence Nonlinear systems nationallicence Optimal control nationallicence Self organising maps nationallicence https://doi.org/10.1007/s005210070022 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s005210070022 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Delgado A. Electrical and Electronics Engineering Department, National University of Colombia, Bogota, Colombia, CO aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer