ACS318   System Identification   (10 credits)

Description

Modelling dynamical systems from first principles via Newton¿s, Kirchoff¿s or other known physical laws is often challenging and costly, requiring substantial expertise. An alternative is offered through ¿system identification¿ that takes observations of inputs and outputs from physical systems and infers or estimates a dynamical model directly. This module introduces two main ways of thinking about the identification problem, the theoretical framework that underpins them and the algorithms that compute the model estimates. It uses synthetic and real problems to illustrate the process and shows how models can be validated for future use.

Reading List