Nonlinear dynamic modelling of a gas engine using an RBF-network

A Radial Basis Function network (RBFN) is used to obtain a model of a gas e ngine, an unstable two-input/single-output system (MISO-system), to be used for the design of the speed control system. The RBFN-centers are chosen us ing the stepwise orthogonalization algorithm, and an input space compressio n which helps to avoid sparse data sets is presented. The influence of nois y data is investigated in a nonlinear system example, in order to find the cause of the model errors in the case of the gas engine model. The quality of the nonlinear RBFN-model is demonstrated by comparing measured and simul ated data.