Echo-state-network-based iterative learning control of distributed systems - Patan, Krzysztof; Patan, Maciej (1975- )
The paper proposes an effective modeling and control procedure for the distributed-parameter systems using the echo-state network. The main idea is to reconstruct the spatio-temporal dynamics defined in a given multi-dimensional domain. In the investigated problem positions of both sensors and actuators are fixed allowing to delegate the complex system dynamics to echo-state network. Imposing a proper partitioning of the spatial domain, a specific topology of a neural network is used to form a reservoir capable to follow not only temporal but also spatial dynamics of the system.
Keywords: adaptive systems; control system design; distributed-parameter system; iterative learning control; modeling; neural networks; training