Stochastic Input-to-state Stability Research Articles

Input-to-state stability of stochastic nonlinear system with delayed impulses.

Stochastic input-to-state stability (SISS) of the stochastic nonlinear system has received extensive research. This paper aimed to investigate SISS of the stochastic nonlinear system with delayed impulses. First, when all subsystems were stable, using the average impulsive interval method and Lyapunov approach, some theoretical conditions ensuring SISS of the considered system were established. The SISS characteristic of the argumented system with both stable and unstable subsystems was also discussed, then the stochastic nonlinear system with multiple delayed impulse jumps was considered and SISS property was explored. Additionally, it should be noted that the Lyapunov rate coefficient considered in this paper is positively time-varying. Finally, several numerical examples confirmed validity of theoretical results.

Dynamic Event-Based Control for Stochastic Optimal Regulation of Nonlinear Networked Control Systems.

In this article, a dynamic event-triggered stochastic adaptive dynamic programming (ADP)-based problem is investigated for nonlinear systems with a communication network. First, a novel condition of obtaining stochastic input-to-state stability (SISS) of discrete version is skillfully established. Then, the event-triggered control strategy is devised, and a near-optimal control policy is designed using an identifier-actor-critic neural networks (NNs) with an event-sampled state vector. Above all, an adaptive static event sampling condition is designed by using the Lyapunov technique to ensure ultimate boundedness (UB) for the closed-loop system. However, since the static event-triggered rule only depends on the current state, regardless of previous values, this article presents an explicit dynamic event-triggered rule. Furthermore, we prove that the lower bound of sampling interval for the proposed dynamic event-triggered control strategy is greater than one, which avoids the so-called triviality phenomenon. Finally, the effectiveness of the proposed near-optimal control pattern is verified by a simulation example.

The Stochastic Robustness of Nominal and Stochastic Model Predictive Control

In this work, we establish and compare the stochastic and deterministic robustness properties achieved by nominal model predictive control (MPC), stochastic MPC (SMPC), and a proposed constraint-tightened MPC (CMPC) formulation, which represents an idealized version of tube-based MPC. We consider three definitions of robustness for nonlinear systems and bounded disturbances: robust asymptotic stability (RAS), robust asymptotic stability in expectation (RASiE), and RASiE w.r.t. the stage cost <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell (\cdot)$</tex-math></inline-formula> used in these MPC formulations ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> -RASiE). Via input-to-state stability (ISS) and stochastic ISS (SISS) Lyapunov functions, we establish that MPC, subject to sufficiently small disturbances, and CMPC ensure all three definitions of robustness without a stochastic objective function. While SMPC also ensures RASiE and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> -RASiE, SMPC does not guarantee RAS for nonlinear systems. Through a few simple examples, we illustrate the implications of these results and demonstrate that, depending on the definition of robustness considered, SMPC is not necessarily more robust than nominal MPC even if the disturbance model is exact.

Exponential input-to-state stability for neutral stochastic delay differential equations with Lévy noise and Markovian switching

This paper mainly focuses on the pth ()-moment input-to-state stability (ISS) of neutral stochastic delay differential equations (NSDDEs) with Lévy noise and Markovian switching. By using the generalized integral inequality and the Lyapunov function methodology, the ISS, integral input-to-state stability (iISS), and stochastic input-to-state stability (SISS) of such equations are obtained. When the input signal is a constant signal and a zero signal, the pth ()-moment ISS reduces to the pth ()-moment practical exponential stability and the pth ()-moment exponential stability, respectively. Finally, an example of the mass–spring–damping (MSD) model under the stochastic perturbation is given to verify the validity of the results.

Nonlinear Stochastic Model Predictive Control: Existence, Measurability, and Stochastic Asymptotic Stability

In this article, we establish a collection of new theoretical properties for nonlinear stochastic model predictive control (SMPC). Based on the concept of stochastic input-to-state stability (SISS), we define robust asymptotic stability in expectation (RASiE) and establish that nonlinear SMPC renders the origin of the closed-loop system RASiE. Moreover, we establish several new foundational results that have not been addressed in previous research. Specifically, we verify that, under basic regularity assumptions, a solution to the SMPC optimization problem exists and the closed-loop trajectory is Borel measurable thereby guaranteeing that all relevant stochastic properties of the closed-loop system are indeed well-defined. We present a numerical example to demonstrate the nonintuitive behavior that can arise from nonlinear SMPC.

Stochastic input-to-state stability for stochastic complex dynamical control networks with impulsive perturbation

In this paper, stochastic input-to-state stability (SISS) for stochastic complex dynamical control networks with impulsive perturbation (SCDCNIP) is investigated. An appropriate global Lyapunov function is developed which is closely related to topology of SCDCNIP and dynamical behaviors of every node system of SCDCNIP. Some sufficient criteria are given to guarantee SCDCNIP to meet SISS by imposing the average dwell-time (ADT) condition and reverse average dwell-time (RADT) condition. Moreover, as an application of our theoretical results, typical stochastic coupled oscillators with impulsive perturbation (SCOIP) are studied. Finally, some numerical simulation results are provided to verify the correctness and validity of our results.

Command filter based adaptive DSC of uncertain stochastic nonlinear systems with input delay and state constraints

In this paper, a command filter based dynamic surface control (DSC) is developed for stochastic nonlinear systems with input delay, stochastic unmodeled dynamics and full state constraints. An error compensation system is designed to constrain the filtering error caused by the first-order filter in the traditional dynamic surface design. On this basis, the stability proof of DSC for stochastic nonlinear systems based on command filter is proposed. The definition of state constraints in probability is presented, and the problem of stochastic full state constraints is solved by constructing a group of coordinate transformations with nonlinear mappings. The Pade approximation is adopted to deal with input delay. The stochastic unmodeled dynamics is considered, which is processed by utilizing the property of stochastic input-to-state stability (SISS) and changing supply function. All the signals of the system are proved to be semi-globally uniformly ultimately bounded (SGUUB) in probability, and the full state constraints are not violated. The two simulation examples also verify the effectiveness of the proposed adaptive DSC scheme.

Improved Input-to-State Stability Analysis of Impulsive Stochastic Systems

This article is concerned with the input-to-state stability (ISS) and stochastic input-to-state stability (SISS) of impulsive stochastic nonlinear systems. By constructing a general SISS-Lyapunov function, which takes the exponential SISS-Lyapunov function as a special case, the ISS criteria are obtained, respectively, for destabilizing and stabilizing impulses. It should be stressed that we impose the average dwell-time (ADT) condition for destabilizing impulses and reverse average dwell-time (RADT) condition for stabilizing impulses to restrain the occurrence of impulses, which extends the fixed dwell-time condition in recent literature. Moreover, the ADT and RADT conditions in this article correspond to the average impulsive interval method in most existing results under the exponential ISS-Lyapunov condition. As a subsequent result, the ISS and SISS of impulsive stochastic interconnected systems on networks are also studied by the Lyapunov method and graph-theoretic technique. Finally, several illustrative examples together with their numerical simulations are provided to demonstrate the theoretical results.

Input-to-State Stability and Stabilization of Sampled-Data Systems Under Aperiodic Sampling and Random Sampling

In this article, input-to-state stability (ISS) and stabilization are examined for sampled-data systems under deterministic aperiodic sampling and random sampling, respectively. Using the direct design method, the sampled-data systems are transformed into switched systems with switched time-varying delays. First, the ISS definition and criterion appropriate for these systems are provided. Based on this, the ISS criterion on sampled-data systems under deterministic aperiodic sampling is given. Second, after the stochastic ISS (SISS) definition and criterion are provided for switched nonlinear systems with randomly switching delays, the SISS criterion for the sampled-data systems under random sampling is provided. All of the ISS and SISS definitions are given in the form of $\mathcal {KL}$ function that is quite elegant and easy to work with. Then, sufficient conditions for input-to-state stabilization are obtained for sampled-data linear systems under deterministic aperiodic sampling and random sampling, respectively, via the Lyapunov-Krasovskii method. Finally, based on the criteria, a piecewise controller is designed by the matrix inequality approach for a sampled-data linear time invariant system, and simulation results are provided to illustrate our design method. The main conclusion of this article is that sampling intervals will affect the controller design of the systems, and the ISS properties are maintained using a piecewise controller.

Stochastic Input-to-State Stability of Impulsive Stochastic Nonlinear Systems in Infinite Dimensions

This paper studies the stochastic input-to-state stability (SISS) of a class of impulsive stochastic nonlinear systems in Hilbert spaces. By constructing a class of proper Yosida strong solution ap...

Input-to-state Stability of Impulsive Stochastic Nonlinear Systems Driven by G-Brownian Motion

This paper studies the input-to-state stability (ISS), stochastic input-to-state stability (SISS) and eλt-weighted input-to-state stability (eλt-ISS) of impulsive stochastic nonlinear systems driven by G-Brownian motion (IGSNSs). If the continuous stochastic systems are not ISS, the impulsive effects can stabilize the system for the fixed dwell-time sequences. However, if the continuous stochastic systems are ISS, the hybrid system can achieve ISS for destabilizing impulses with upper bound of the fixed dwell-time. Moreover, the average dwell-time condition is generalized to guarantee the ISS for IGSNSs based on G-Lyapunov method. Finally, an example is provided to illustrate the effectiveness of theoretical results.

Stability analysis for switched stochastic delayed systems under asynchronous switching: A relaxed switching signal

SummaryThis article deals with the stochastic input‐to‐state stability (SISS) for a class of switched stochastic systems under asynchronous switching. Asynchronous switching refers to that the switching of the candidate controllers does not coincide with the switching of system modes. In addition, the time delays appear in the state. Unlike the existing works, we not only allow the coefficients of the estimated upper bound for the diffusion operator of a Lyapunov function to be increasing during the matched time interval, but also in the unmatched time interval. Meanwhile, by using the switching signals which prevail over the traditional average dwell time scheme and the Razumikhin theorem, the SISS property is obtained. Especially our results improve some existing ones regarding asynchronous switching in the literature. Two examples are used to demonstrate the applicability of the results.

A new unified input‐to‐state stability criterion for impulsive stochastic delay systems with Markovian switching

SummaryIn this paper, the problems of the input‐to‐state stability (ISS), the integral input‐to‐state stability (iISS), the stochastic input‐to‐state stability (SISS) and the eλt(λ&gt;0)‐weighted input‐to‐state stability (eλt‐ISS) are investigated for nonlinear time‐varying impulsive stochastic delay systems with Markovian switching. We propose one unified criterion for the stabilizing impulse and the destabilizing impulse to guarantee the ISS, iISS, SISS and eλt‐ISS for such systems. We verify that when the upper bound of the average impulsive interval is given, the stabilizing impulsive effect can stabilize the systems without ISS. We also show that the destabilizing impulsive signal with a given lower bound of the average impulsive interval can preserve the ISS of the systems. In addition, one criterion for guaranteeing the ISS of nonlinear time‐varying stochastic hybrid systems under no impulsive effect is derived. Two examples including one coupled dynamic systems model subject to external random perturbation of the continuous input and impulsive input disturbances are provided to illustrate the effectiveness of the theoretic results developed.

Stochastic input-to-state stability for impulsive switched stochastic nonlinear systems with multiple jumps

ABSTRACTIn this study, we investigate the stochastic input-to-state stability (SISS) of impulsive switched stochastic nonlinear systems. In this model, the impulse jumps are component multiple maps that depend on time. Thus the model differs from traditional impulsive systems with single impulse between two adjacent switching times. We provide sufficient conditions in three cases with the SISS system by using the Lyapunov function and average impulsive interval approach. The destabilising impulses cannot destroy the SISS properties if the impulses do not occur too frequently when all the subsystems that control the continuous dynamics are SISS. In other words, the average impulsive interval satisfies a lower bound restraint. Conversely, when all subsystems that control the continuous dynamics are not SISS, impulses can contribute to stabilising the system in the SISS sense when the average impulsive interval satisfies an upper bound. Then, we investigate the SISS property of impulsive switched stochastic nonlinear systems with some subsystems that are not SISS under certain conditions such that the property remains obtained. Finally, we show three examples to demonstrate the validity of the main result.

Input-to-state stability for impulsive stochastic nonlinear systems with delayed impulses

In this paper, the problems of the stochastic input-to-state stability (SISS) properties are investigated for impulsive stochastic nonlinear systems with delayed impulses. By employing Lyapunov method together with average impulsive interval approach, the sufficient conditions are established to ensure properties for impulsive stochastic systems with all stable subsystems. Moreover, the ISS properties are also derived for the stochastic systems when the system is with both stable and unstable subsystems. Then, we also study impulsive systems with multiple jumps, i.e. there exist different impulses in a system. By now, there has been no papers to consider multiple jumps for stochastic cases. Finally, two examples are provided to illustrate the effectiveness of our results.

Input‐to‐state stability of stochastic port‐Hamiltonian systems using stochastic generalized canonical transformations

SummaryAs a practically important class of nonlinear stochastic systems, this paper considers stochastic port‐Hamiltonian systems (SPHSs) and investigates the stochastic input‐to‐state stability (SISS) property of a class of SPHSs. We clarify necessary conditions for the closed‐loop system of an SPHS to be SISS. Moreover, we provide a systematic construction of both the SISS controller and Lyapunov function so that the proposed necessary conditions hold. In the main results, the stochastic generalized canonical transformation plays a key role. The stochastic generalized canonical transformation technique enables to design both coordinate transformation and feedback controller with preserving the SPHS structure of the closed‐loop system. Consequently, the main theorem guarantees that the closed‐loop system obtained by the proposed method is SISS against both deterministic disturbance and stochastic noise. Copyright © 2017 John Wiley &amp; Sons, Ltd.

Nonfragile RobustH∞Filter Design for a Class of Fuzzy Stochastic Systems with Stochastic Input-to-State Stability

The nonfragileH∞filtering problem for a kind of Takagi-Sugeno (T-S) fuzzy stochastic system which has a time-varying delay and parameter uncertainties has been studied in this paper. Sufficient conditions for stochastic input-to-state stability (SISS) of the fuzzy stochastic systems are obtained. Attention is focused on the design of a nonfragileH∞filter such that the filtering error system can tolerate some level of the gain variations in the filter and theH∞performance level also could be satisfied. By using the SISS result, the approach to design the nonfragile filter is proposed in terms of linear matrix inequalities. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

On input-to-state stability of impulsive stochastic systems

This paper is concerned with the input-to-state stability (ISS) of impulsive stochastic systems. First, appropriate concepts of stochastic input-to-state stability (SISS) and pth moment input-to-state stability (p-ISS) for the mentioned systems are introduced. Then, we prove that impulsive stochastic systems possessing SISS-Lyapunov functions are uniformly SISS and p-ISS over a certain class of impulse sequences. As a byproduct, a criterion on the uniform global asymptotic stability in probability for the system in isolation (without inputs) is also derived. Finally, we provide a numerical example to illustrate our results.

On Input-to-State Stability of Impulsive Stochastic Systems with Time Delays

This paper is concerned withpth moment input-to-state stability (p-ISS) and stochastic input-to-state stability (SISS) of impulsive stochastic systems with time delays. Razumikhin-type theorems ensuringp-ISS/SISS are established for the mentioned systems with external input affecting both the continuous and the discrete dynamics. It is shown that when the impulse-free delayed stochastic dynamics arep-ISS/SISS but the impulses are destabilizing, thep-ISS/SISS property of the impulsive stochastic systems can be preserved if the length of the impulsive interval is large enough. In particular, if the impulse-free delayed stochastic dynamics arep-ISS/SISS and the discrete dynamics are marginally stable for the zero input, the impulsive stochastic system isp-ISS/SISS regardless of how often or how seldom the impulses occur. To overcome the difficulties caused by the coexistence of time delays, impulses, and stochastic effects, Razumikhin techniques and piecewise continuous Lyapunov functions as well as stochastic analysis techniques are involved together. An example is provided to illustrate the effectiveness and advantages of our results.

Stochastic input-to-state stability and [formula omitted] filtering for a class of stochastic nonlinear systems

In this paper, an H∞ filtering problem is considered for a class of stochastic nonlinear systems with time-delay and exogenous disturbances. Sufficient conditions for stochastic input-to-state stability (SISS) of the stochastic nonlinear systems are developed via Lyapunov function method and linear matrix inequalities (LMIs) technique. The purpose of this work is to design a nonlinear filter to ensure both the SISS and a prescribed H∞ attenuation level for the corresponding filtering error system. By using the SISS results, a set of sufficient conditions for the existence of H∞ filter is given in the form of LMI. When the LMI is feasible, an explicit expression of a desired filter is presented. Finally, some numerical and practical examples are employed to demonstrate the effectiveness of the proposed approaches.