The adaptation of perceptrons with applications to inverse dynamics identification of unknown dynamic systems

The authors propose a new class of adaptation algorithms for single- and multilayer perceptrons with discontinuous nonlinearities. The behavior of the proposed algorithms is shown on an application example and simulation results are included. The simulations were performed using the SIMNON package developed for purpose of simulation of nonlinear systems. The results can be used to control unknown dynamic systems using neural controllers. Indeed, many robust control algorithms utilize the inverse dynamics of the plant to be controlled. Thus, the proposed structures where the perceptrons are the inverse system model identifiers should constitute a part of the controller