Dynamic recurrent neural network for system identification and control
A. Delgado, C. Kambhampati, Kevin Warwick · IEE Proceedings - Control Theory and Applications · 1995
A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.