A nonlinear control system comprising a network of networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. The neural networks are initialized algebraically by observing that the gradients of the networks must equal corresponding linear gain matrices at chosen operating points. On-line learning is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for plant dynamics and nonlinear effects. The result is an adaptive controller that is as conservative as the linear designs and as effective as the global controller. The design method is implemented to control the full six-degree-of-freedom simulation of a business jet aircraft.
|Original language||English (US)|
|Title of host publication||Proceedings of the American Control Conference|
|Number of pages||6|
|State||Published - Jan 1 2002|
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering