Decentralized robust adaptive controller of modular stochastic control systems

We study the decentralized robust adaptive tracking problem of control systems consisting of n modular subsystems with stochastic input terms. A nonlinear control scheme for stochastic linear control systems is proposed to design the direct adaptive controller for each modular stochastic subsystem. When the stochastic input terms satisfy some assumptions, we prove that the output tracking error of the closed-loop control systems is globally and asymptotically bounded and can be guaranteed to converge to within the precision prescribed in the actual problems. Finally, an efficient decentralized control algorithm is employed to solve a simulation example.