Decentralized stabilization of large-scale stochastic nonlinear systems with time-varying powers

Output-feedback stabilization for stochastic nonlinear systems whose linearizations are not stabilizable

Mean-square practical stability for stochastic large-scale dynamical systems is studied. The vector Lyapunov functions and the basic comparison principle of stochastic systems as well as the decomposition-aggregation method for large-scale systems were used to obtain results for various types of mean-square practical stability of nonlinear stochastic large-scale dynamical systems. The objective is to analyze stochastic large-scale systems in terms of their lower-order subsystems and in terms of their interconnecting structure. These results make it possible to determine the mean-square practical stability of stochastic large-scale dynamical systems by testing the corresponding practical stability of the auxiliary deterministic systems. >

This paper considers a more general stochastic nonlinear time-delay system driven by unknown covariance noise and investigates its adaptive state-feedback control problem. As a remarkable feature, the growth assumptions imposed on delay-dependent nonlinear terms are removed. Then, with the help of Lyapunov-Krasovskii functionals and adaptive backstepping technique, an adaptive state-feedback controller is constructed by overcoming the negative effects brought by unknown time delay and covariance noise. Based on the designed controller, the closed-loop system can be guaranteed to be globally asymptotically stable (GAS) in probability. Finally, a simulation example demonstrates the effectiveness of the proposed scheme.

This note is devoted to study the stabilization problem of stochastic nonlinear delay systems with exogenous disturbances and the event-triggered feedback control. By introducing the notation of input-to-state practical stability and an event-triggered strategy, we establish the input-to-state practically exponential mean-square stability of the suggested system. Moreover, we investigate the stabilization result by designing the feedback gain matrix and the event-triggered feedback controller, which is expressed in terms of linear matrix inequalities. Also, the lower bounds of interexecution times by the proposed event-triggered control method are obtained. Finally, an example is given to show the effectiveness of the proposed method. Compared with a large number of results for discrete-time stochastic systems, only a few results have appeared on the event-triggered control for continuous-time stochastic systems. In particular, there have been no published papers on the event-triggered control for continuous-time stochastic delay systems. This note is a first try to fill the gap on the topic.

We study the problem of output feedback stabilization for stochastic nonlinear systems. We consider a class of stochastic nonlinear systems in observer canonical form with stable zero-dynamics. We introduce a sequence of state transformations that transform the system into a lower triangular structure that is amenable for integrator backstepping design. Then we design the output feedback controller and prove that the closed-loop system is bounded in probability. Under an infinite-horizon risk-neutral cost criterion, the controller designed can guarantee an arbitrarily small long term average cost. Furthermore, when the disturbance vector field vanishes at the origin, the closed-loop system is asymptotically stable in the large, and the risk-neutral cost is guaranteed to be zero. With special care, the controller preserves the equilibrium of the nonlinear system.

Backstepping-based decentralized bounded-H∞ adaptive neural control for a class of large-scale stochastic nonlinear systems

Global stabilization of stochastic high-order feedforward nonlinear systems with time-varying delay

New criteria of almost sure exponential stability and instability of nonlinear stochastic systems with a generalization to stochastic coupled systems

Adaptive fuzzy decentralized control for stochastic large-scale nonlinear systems with unknown dead-zone and unmodeled dynamics

This paper discusses the problem of adaptive stabilization for stochastic feedforward nonlinear systems with time-delay. A universal-type adaptive update law is introduced into the observer and controller to deal with unknown growth rates. With the help of the appropriate Lyapunov-Krasovskii functional and stochastic Barbalat's lemma, it can be proved that the universal-type adaptive output feedback controller can regulate all the states of the closed-loop system almost surely. A simulation example is given to illustrate the effectiveness of the proposed method.

The homogeneous domination approach is introduced to solve the state feedback stabilization problem for stochastic high-order nonlinear systems with time-varying delay. Under the weaker conditions on the drift and diffusion terms, by using the homogeneous domination approach and solving several troublesome obstacles in the design and analysis procedure, a state feedback controller is constructed to render the closed-loop system globally asymptotically stable in probability.

Adaptive decentralized NN control of large-scale stochastic nonlinear time-delay systems with unknown dead-zone inputs

This paper addresses the problem of state feedback control for a class of stochastic high-order feedforward nonlinear systems with multiple time-varying delays. A distinct property of the system to be investigated is that the control coefficients are not restricted to 1. By introducing the sign function and the adding one power integrator, a delay-independent state feedback controller is constructed. By Lyapunov-Krasovskii theorem and homogeneous domination approach, the global stochastic asymptotic stability of the closed-loop system under the above-mentioned controller is proved. Finally, a simulation example is given to illustrate the effectiveness of the results of this paper.

The robust stability problem for nonlinear distributed delay stochastic systems with polytopic-type uncertainties is discussed. Based on parameter-dependent Lyapunov-krasovs-kii functional and free-weighting matrix method, a delay-dependent and parameter-dependent stability condition is presented in terms of linear matrix inequalities. The result in this paper improves the existing stability criteria and has less conservativeness. The simulation example shows that the result is effective.

This paper is concerned with the stabilization problem for nonlinear stochastic delay systems with Markovian switching by feedback control based on discrete-time state and mode observations. By constructing an efficient Lyapunov functionals, we establish the sufficient stabilization criteria not only in the sense of exponential stability (both the mean-square stability and the almost sure stability) but also in other sense – that of stability and asymptotic stability. Meanwhile, the upper bound on the duration τ between two consecutive state and mode observations is obtained. Numerical examples are provided to demonstrate the effectiveness of our theoretical results.