Stabilization Of Stochastic Nonlinear Systems Research Articles

Stability analysis for stochastic nonlinear systems with state-dependent switching and time-delay

The stability of stochastic nonlinear systems with time-delay and state-dependent switching is studied in this paper. Firstly, system maximal solution is constructed and further extended as the global solution under certain mild conditions. Secondly, several Krasovskii-type stability and Razumikhin-type theorems are proposed by uniformly asymptotically stable functions (UASFs). These stability criteria overcome some stringent constraints associated with Lyapunov functional/functions. Finally, the theoretical findings are validated through two simulation examples.

Predefined-time stabilization of stochastic nonlinear systems with application to UAVs

The paper presents a new Lyapunov-type predefined-time stabilization control algorithm for stochastic high-order nonlinear systems with asymmetric output constraints. In contrast to stochastic finite-time and fixed-time stabilization, the average value of the settling-time function for stochastic predefined-time stabilization control is independent of both the initial value and the control factors. To mitigate the significant uncertainties arising from the asymmetric output constraint, a tan-type barrier Lyapunov function is formulated. Furthermore, by harnessing the previously mentioned barrier Lyapunov function and integrating the power integrator technique, a controller design strategy is formulated based on the backstepping method. The rigorous analysis in this study proves that the designed controller ensures both the attainment of predefined-time convergence of the system states to the origin in probability and the satisfaction of the output constraint. Finally, an example of a roll angle subsystem for quadrotor UAVs and a numerical illustration are presented to corroborate the theoretical analysis.

Stabilization of nonlinear stochastic systems with input and output delays via event‐triggered predictive control

AbstractThe stabilization of nonlinear stochastic systems with input and output delays is investigated in this article. First, an observer that includes input delay information is designed to estimate the state information after eliminating the effect of input delay. Second, a predictive scheme with delay information is utilized to predict the system state affected by output delay, and an event‐triggered predictive controller is established to eliminate the effects of input and output delays simultaneously. Subsequently, the convergence of the prediction error is analyzed by utilizing a recursive method, and a sufficient condition to ensure the global exponential stability is given by constructing a new closed‐loop system. Finally, numerical simulations of two nonlinear stochastic systems with different delay sizes are utilized to verify the impact of the event‐triggered predictive control in addressing the stabilization of nonlinear stochastic systems with time delays.

Semi-global exponential stabilization of stochastic nonlinear systems with distributed delay under discrete-time state observations and application to circuit systems

This paper is aimed at studying the semi-global exponential stabilization problem for stochastic nonlinear systems with distributed delay under discrete-time state observations. An extended definition of horizontal translation of the segment function along the investigated systems is given, related to the stochastic disturbance and Brownian motion. Basically, the right and upper Dini’s derivative of the constructed functional is presented. Combining this with the global exponential stability of the stochastic nonlinear systems with distributed delay under continuous-time feedback control, the Lyapunov method and Halanay inequality, the maximum observation interval and some stabilization criteria to make the investigated systems under discrete-time state observations reach semi-global exponential stabilization are provided. The results indicate that the semi-global exponential stabilization is dependent upon stochastic disturbance, initial condition range, and maximum observation interval. Finally, an application to the circuit systems is discussed and the involved sufficient conditions for the circuit systems to keep semi-global stabilization are also proposed. Besides, the numerical simulation results confirm the effectiveness of the theoretical results.

Finite-Time Stabilization of Stochastic Nonlinear Systems and Its Applications in Ship Maneuvering Systems

Finite-Time Stabilization of Stochastic Nonlinear Systems and Its Applications in Ship Maneuvering Systems

Finite-time stochastic integral input-to-state stability and its applications

In this paper, finite-time stabilization is investigated in depth for stochastic nonlinear systems with stochastic inverse dynamics. The contributions of this work are characterized by the following novel features: (i) Motivated by the concept of stochastic integral input-to-state stability (SiISS) and the existing stochastic finite-time stability theorem, a new concept of finite-time stochastic integral input-to-state stability (FT-SiISS) using Lyapunov function is first introduced, and an inclusion relationship among three types of stochastic stability, i.e., FT-SiISS, FT-SISS and SISS, is rigorously established. On the basis of FT-SiISS, we develop two new FT-SiISS small-gain conditions and discuss their relationship. Then, to analyze finite-time stability of stochastic nonlinear systems with FT-SiISS inverse dynamics, a stochastic finite-time stability theorem is improved. (ii) As the application of (i), we propose a unified finite-time control method, which can simultaneously handle stochastic nonlinear systems with FT-SiISS or FT-SISS inverse dynamics, and guarantee that the closed-loop system has an almost surely continuous solution, all the closed-loop signals are bounded almost surely, and its trivial solution is stochastically finite-time stable.

Stochastic finite-time stability and stabilization for stochastic nonlinear systems with impulse effects

In this paper, some unified stochastic finite-time stability (SFTS) criteria are derived for the impulsive stochastic nonlinear systems by using the stochastic analysis theory, stopping time technology, Lyapunov approach and limit average dwell time (LADT) technology when the impulse effect is destabilizing impulse or stabilizing impulse. Meanwhile, in order to achieve stochastic finite-time stabilization for stochastic nonlinear systems, the impulse control approach is also obtained, which can be divided into two cases: (1) A stochastic finite-time instable (SFTI) stochastic system can become SFTS under the impulse control strategy; (2) A SFTS stochastic system can keep the SFTS under the impulsive disturbance. Furthermore, by using the impulse dependent average dwell time (IDADT) technology, the results are also established for the multiple impulse effects, i.e. destabilizing impulse and stabilizing impulse exist in the system simultaneously. Finally, two useful examples are provided.

Stability and Stabilization of Nonlinear Stochastic Systems With Synchronous and Asynchronous Switching Parameters to the States.

This article is concerned with the stability and stabilization of nonlinear hybrid stochastic systems. First, the concepts of synchronous and asynchronous switching parameters to the system states are proposed for a generalization of the asynchronous control. As preliminaries, a hybrid nonlinear differential inequality is established for coping with the synchronous models, and the -continuity of the system parameters driven by Markov chains is established for coping with the asynchronous models by the attribute of Markov chains for less conservativeness. Second, stability criteria with moment exponential estimates are established for two kinds of system models under the nonlinear growth condition. Third, the stabilization problem is illustrated based on the stability criteria and Riccati like matrix equations. A corollary is given to improve some stability theorems obtained in the related literature. New initial condition is formally proposed and explained for the nonlinear stochastic systems. Finally, a numerical example with simulation is proposed to illustrate the method, verify the conclusions of this article, and show the superiority of this work.

Fixed-Time Lyapunov Criteria of Stochastic Nonlinear Systems and Its Generalization

This study investigates the fixed-time stability of stochastic nonlinear systems described by Itô differential equations. The improved fixed-time Lyapunov theorem is given and an important corollary is obtained. It is proved that the upper-bound estimate of the settling time is less conservative. We establish a new definition of practically fixed-time stability in probability (PFxTSp) and propose the corresponding Lyapunov criterion theorem. In addition, different cases of the parameters are discussed to provide a less conservative upper-bound estimate of the settling time. The effectiveness of the proposed stability and controller is demonstrated by two simulation examples.

Prescribed-time stabilization control for p-norm stochastic nonlinear systems based on homogeneous dominant technique

In this article, a prescribed-time state-feedback stabilization design strategy is proposed for a class of p-norm stochastic nonlinear strict feedback systems. In previous work on prescribed-time stabilization of stochastic systems, only stochastic nonlinear systems with fractional power less than or equal to one are considered. To overcome this problem, we improve the existing method and discuss the issue of prescribed-time stabilization of stochastic nonlinear systems with fractional power is arbitrary positive odd rational number. First, a prescribed-time controller is designed by combining the Lyapunov function with adding a power integrator technique. It should be pointed out that the homogeneous domination approach is adopted when dealing with the nonlinear terms of the system. Then, according to the stochastic prescribed-time stability theorem, it is proved that the designed controller can ensure the closed-loop system is prescribed-time mean-square stable. Finally, three simulation examples are given to investigate the validity of the presented method, in which the last one is an electromechanical system example.

Global Output Feedback Stabilization for Stochastic Nonlinear Systems with Multiple Uncertainties

Global Output Feedback Stabilization for Stochastic Nonlinear Systems with Multiple Uncertainties

Domain stabilization in probability in a fixed time for nonlinear stochastic systems via feedback control

AbstractThis paper is concerned with the domain stabilization in probability in a fixed time for nonlinear stochastic systems. More specifically, given a target domain , a probability and a fixed time , we aim to find suitable state feedback control laws such that the trajectory of the resulting closed‐loop system, starting from outside , will reach the target domain in the fixed time with the minimum probability . To this end, we prove a local existence and uniqueness result of solutions to nonlinear stochastic systems under mild conditions, and derive upper bounds of the mean of the first hitting time with respect to under various rigorous conditions. By these results, a Lyapunov‐based controller design is given to guarantee the domain stability for nonlinear stochastic systems with affine control inputs. Besides, inequalities of quadratic forms focusing on semi‐linear stochastic systems are used to design a linear state feedback controller for achieving the domain stability in probability. Several examples are given for demonstration.

Fast finite time stability of stochastic nonlinear systems

This paper focus on fast finite time stability for a class of stochastic nonlinear systems. Firstly, a useful inequality, which will play a crucial role in the fast finite time stability in probability, is expanded on Bihari inequality. Then, the concept of fast finite time stability is discussed for stochastic nonlinear systems and an important theory concerned with fast finite time stability in probability is obtained. Next, a fast finite time state feedback controller can be subtle designed, which not only shortens the convergent time but also requires no large control effort. Three simulation examples are given to support our results of theoretical analysis.

Adaptive State-Feedback Stabilization for Stochastic Nonlinear Systems with Time-Varying Powers and Unknown Covariance

This paper investigates the adaptive state-feedback stabilization problem for stochastic nonlinear systems. Compared with the existing results, we consider more general and more practical systems, i.e., systems with time-varying powers and unknown covariance simultaneously. We propose a new adaptive state-feedback control method, which ensures that the closed-loop system is globally stable in probability and the states are regulated to the origin almost surely. Finally, the feasibility of the design method is verified by two examples.

Incremental nonlinear stability analysis of stochastic systems perturbed by Lévy noise

AbstractWe present a theoretical framework for characterizing incremental stability of nonlinear stochastic systems perturbed by either compound Poisson shot noise or finite‐measure Lévy noise. For each noise type, we compare trajectories of the perturbed system with distinct noise sample paths against trajectories of the nominal, unperturbed system. We show that for a finite number of jumps arising from the noise process, the mean‐squared error between the trajectories exponentially converge toward a bounded error ball across a finite interval of time under practical boundedness assumptions. The convergence rate for shot noise systems is the same as the exponentially stable nominal system, but with a tradeoff between the parameters of the shot noise process and the size of the error ball. The convergence rate and the error ball for the Lévy noise system are shown to be nearly direct sums of the respective quantities for the shot and white noise systems separately, a result which is analogous to the Lévy–Khintchine theorem. We demonstrate both empirical and analytical computation of the error ball using several numerical examples, and illustrate how varying the parameters of the system affect the tightness of the bound.

On the simultaneous stabilization of stochastic nonlinear systems

SummaryIn this paper, the problem of simultaneous stabilization in probability by state feedback is investigated for a class of stochastic nonlinear systems whose drift and diffusion terms are dependent on the control and for which classical methods are not applicable. Under the assumption that a collection of stochastic control Lyapunov functions (SCLFs) is known and based on the generalized stochastic Lyapunov theorem, we derive sufficient conditions for the simultaneous stabilization in probability by a continuous state feedback controller that we explicitly compute. We also derive a necessary condition when the system coefficients satisfy some regularity conditions. This work generalizes previous results on the simultaneous stabilization of stochastic nonlinear systems. The obtained results are illustrated by a numerical example.

Stochastic Finite-Time Stability for Stochastic Nonlinear Systems with Stochastic Impulses

In this paper, some novel stochastic finite-time stability criteria for stochastic nonlinear systems with stochastic impulse effects are established. The results in this paper blackgeneralized the related results in from two aspects: 1. the model in is the deterministic systems, which means that the noise effect that can be described as a symmetric Markov process Brownian motion is considered in our models; 2. the stochastic finite-time stability criterion is established in this paper, not the asymptotic stability and the input-to-state stability that are studied in the form literature. Finally, an example is given to show the significance blackand usefulness of our results.

Event-triggered predictive control of nonlinear stochastic systems with output delay

In this paper, we focus on the stabilization of nonlinear stochastic systems with output delay. Based on the predictive scheme and event-triggering mechanism (ETM), a novel event-triggered predictive control is proposed to exponentially stabilize such stochastic systems. Moreover, this novel control law allows non-uniform sampled measurements and large delays involved in the output. Simultaneously, the control input error induced by ETM is considered and a positive lower bound on the inter-event times is obtained. Finally, an illustrative example is given to demonstrate the obtained results.

Output-Feedback stabilization for stochastic nonlinear systems with Markovian switching and time-varying powers.

This paper investigates the output-feedback stabilization for stochastic nonlinear systems with both Markovian switching and time-varying powers. Specifically, by developing a novel dynamic gain method and using the Itô formula of Markovian switching systems, a reduced-order observer with a dynamic gain and an output-feedback controller are designed. By using advanced stochastic analysis methods, we show that the closed-loop system has an almost surely unique solution and the states are regulated to the origin almost surely. A distinct feature of this paper is that even though there is no Markovian switching, our design is also new since it can deal with nonlinear growth rate, while the existing results can only deal with constant growth rate. Finally, the effectiveness of the design method is verified by a simulation example.

Adaptive Fast Finite-Time Fuzzy Control of Stochastic Nonlinear Systems

This article focuses on the adaptive fast finite-time tracking control for a class of stochastic nonlinear systems. To begin with, an adequate qualification is provided for the practically fast finite-time stability. Then, based upon this adequate qualification, a new adaptive fuzzy control scheme is presented. Due to the stochastic disturbance, criteria of the existing fast finite-time stability cannot be applied to the analysis of the stability of stochastic nonlinear systems. To solve this issue, based on Lemma 6, an original criterion of the fast finite-time stability is constructed first in Lemma 7 by using the theorem of the integral mean value. Meanwhile, it would have a huge impact on the analysis of the fast finite-time stability for stochastic nonlinear systems. Finally, a simulation example is carried out for evaluating the validity of the main result.