Brief Paper: Output-feedback adaptive dynamic surface control of stochastic non-linear systems using neural network

For the first time, a dynamic surface control approach is proposed for a class of stochastic non-linear systems with the standard output-feedback form using neural network. The proposed approach is a stochastic vision of the existing dynamic surface control approach which can overcome the problem of ´explosion of complexity´ in the backstepping design of stochastic systems. Moreover, all unknown system functions are lumped into a suitable unknown function which is compensated for using only a neural network. The proposed control approach is simpler than the existing backstepping control methods for stochastic systems. Two examples are given to illustrate the effectiveness of the proposed design approach.