Decentralized adaptive control of large-scale time-varying stochastic nonlinear systems with unknown covariance
Abstract
In this paper, a novel decentralized adaptive state-feedback design method is proposed for large-scale stochastic nonlinear systems. Different from the existing results, we consider more practical and more general systems, that is, systems with both unknown covariance and time-varying powers. When dealing with the unknown time-varying covariance, we do not need to know its bound, but use the estimator to design an adaptive law function. Then, a new adaptive controller is constructed with the backstepping method to ensure that the closed-loop system is globally stable in probability, and that the states are regulated to the origin almost surely. Finally, a simulation example is given to illustrate the effectiveness of the design scheme.
