Feedback control optimization of nonlinear systems under random excitations

This paper uses stochastic averaging method to design an optimal feedback control for nonlinear stochastic systems. The method of stochastic averaging is used to reduce the dimension of the state space and to derive the Itô stochastic differential equation for the response amplitude process. Two approaches to optimization, namely, with the exact steady state probability density function of the amplitude process and the Rayleigh approximation are compared. The cost function is a steady state response measure. Numerical examples are studied to demonstrate the performance of the control both in transient and steady-state. The effect of the control on the system response and control performance is studied. The regions where the controls are conservative and unconservative are pointed out.