Nonlinear Controller Design for Stochastic Systems

This paper presents methods for achieving a reduction in the computational load required to obtain probability distributions in stochastic systems which do not allow us to assume a Gaussian distribution at the output. The evolution of the probability function can be described by the Fokker-Planck equation Two distinct methods: the numerical method and the eigenfunction expansion method were studied for obtaining a stationary probability density function. Examples are given using the eigenfunction method for nonlinear controller parameter selection.