Stabilization of stochastic nonlinear systems driven by noise of unknown covariance

Adaptive State-Feedback Stabilization for High-Order Stochastic Nonlinear Systems Driven by Noise of Unknown Covariance

Output-Feedback Stabilization of Stochastic Nonlinear Systems Driven by Noise of Unknown Covariance

We address the class of stochastic output-feedback nonlinear systems driven by noise whose covariance is time varying and bounded but the bound is not known a priori. This problem is analogous to deterministic disturbance attenuation problems. We rst design a controller which guarantees that the solutions converge (in probability) to a residual set proportional to the unknown bound on the covar...

A Stabilization Phenomenon for a Class of Stochastic Partial Differential Equations

In this paper we investigate the long-time behavior of solutions to a class of semilinear, stochastic partial differential equations defined on a bounded domain D ⊂ R with smooth boundary ∂D and driven by an infinite-dimensional noise derived from an L(D)-valued Wiener process. We consider the case of a noise with nuclear covariance and we derive the almost sure convergence of solutions to one ...

Stochastic Nonlinear Stabilization|Part I: A Backstepping Design

While the current robust nonlinear control toolbox includes a number of methods for systems aane in a deterministic bounded disturbances, the problem when the disturbance is unbounded stochastic noise has hardly been considered. We present a control design which achieves global asymptotic (Lyapunov) stability in probability for a class of strict-feedback nonlinear continuous-time systems driven...

Adaptive fuzzy pole placement for stabilization of non-linear systems

A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...