Neural network based nonlinear observers

Nonlinear observers based on the well-known concept of minimum energy estimation are discussed. The approach relies an output injection operator determined by a Hamilton–Jacobi–Bellman equation whose solution is subsequently approximated neural network. A suitable optimization problem allowing to learn network parameters proposed and numerically investigated for linear nonlinear oscillators.