Robust H∞ tracking control of output probability density function

A new kind of robust tracking controller of output probability density function (PDF) which satisfies H-infinity disturbance attenuation level is proposed for a class of dynamic stochastic systems. Based on the B-spline neural network model to represent the output PDF, a dynamic weighting model is established, where uncertainties and time-delays are included. Considering the exterior disturbance, we design a robust H-infinity tracking controller via error feedback. The desired controller can not only satisfy the H-infinity disturbance attenuation level, but also realize the perfect tracking and make the closed-loop dynamic stochastic system asymptotically stable and the closed-loop value of linear quadratic cost function satisfy a specified upper bound. The simulation results show that the presented method is valid.