Title :
Continuous-time local state local model networks
Author_Institution :
Centre for Syst. & Control., Glasgow Univ., UK
Abstract :
The continuous-time version of the local model network (LMN) approach of Johansen and Foss is discussed. A distinction is made between local state and global state LMNs; the former turns out to be a form of recurrent net, the latter a form of feedforward net. It is shown how local-state LMN representations of nonlinear systems can be used to design LMN-based controllers via both state observer/feedback. It is suggested that this approach provides an alternative foundation for nonlinear self-tuning control
Keywords :
control system synthesis; feedforward neural nets; nonlinear control systems; observers; recurrent neural nets; self-adjusting systems; state feedback; continuous-time local state local model networks; feedback; feedforward net; global state; local state; nonlinear self-tuning control; nonlinear systems; recurrent net; state observer; Artificial neural networks; Context modeling; Control system synthesis; Control systems; Differential algebraic equations; Differential equations; Nonlinear control systems; Nonlinear equations; Nonlinear systems; State feedback;
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
DOI :
10.1109/ICSMC.1995.537873
