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1.
This paper gives an extension of the Volterra-functional method to the analysis of nonlinear systems with both stochastic input and stochastic parameters. In Section II, first-order linear systems with stochastic input and stochastic parameter are analyzed. Certain definitions and symbolic relations are established. A special example in which the stochastic input and the stochastic parameter are closely related is given in Appendix I. Section III deals with the analysis of first-order nonlinear systems with both stochastic input and stochastic parameter, by means of the Volterra-functional method. A simpler analysis by extension of the Transform-ensemble method is given in Appendix II. Section IV presents the detailed analysis of nonlinear stochastic systems with four illustrative examples. The analysis can be extended to a class of nonlinear stochastic systems with higher-order linear plants with constant or time-varying parameters.  相似文献   

2.
This paper is concerned with the simultaneous exponential stabilization problem for a set of stochastic port-controlled Hamiltonian (PCH) systems. Due to the limited bandwidth of the channels, the phenomena of fading channels and transmission delays which are described by a time-varying stochastic model always occur in the communication channels from the controller to the actuator. Meanwhile, actuator saturation constraint is taken into account. On the basis of dissipative Hamiltonian structural and saturating actuator properties, those stochastic PCH systems are combined to generate an augmented system. By utilizing the stochastic analysis theory, sufficient criterions are given for the simultaneous stabilization controller design ensuring that the closed-loop system is simultaneously exponentially mean-square stable (SEMSS). For the case that there exist external disturbances in the systems, some results on stability analysis and controller design are given. The developed controller design scheme is proved by a three-helicopter model simulation example.  相似文献   

3.
This paper is concerned with the asymptotic stabilization of discrete singular systems over a bandwidth limited digital network, when the state measurements are periodically sampled and encoded using a finite alphabet, and the control input signals are subject to finite-alphabet encoding and Denial-of-Service attacks. It is assumed that the attack signals are uniform for all sampling periods and have been identified. A dynamic controller is designed based on a restricted equivalent model of the controlled plant. Two types of finite-level quantizers are designed for encoding: uniform and logarithmic. For both types of quantizers, dynamic encoding-decoding strategies for the plant state and the control input are proposed, which exploit the controller’s state and the origin, respectively, as the quantization centers. Sufficient conditions for asymptotic stabilizability involving the sampling period, the numbers of the state and input quantization levels, the beginning time and corresponding duration of the attack signals are established by propagating reachable sets during sampling interval. Finally, several numerical examples are given to illustrate the design procedures and the efficacy of the theoretical results.  相似文献   

4.
We study the consensus control of discrete-time second-order multi-agents systems with time delays and multiplicative noises, where the consensus protocol is designed by both the local relative position measurements and each agent’s absolute velocity. Due to the existence of time delays and multiplicative noises, the classical methods for deterministic models with time delays cannot work. In this paper, we apply stochastic stability theorem of discrete-time stochastic delay equations to find some explicit sufficient conditions for both mean square and almost sure consensus. It is proven that for any given noise intensities and time delays, the second-order multi-agent consensus can be achieved by choosing appropriate control gains in the relative position measurement and absolute velocity, respectively. Numerical simulation is given to demonstrate the effectiveness of the proposed protocols as well as the theoretical results.  相似文献   

5.
In this paper, we consider the problem of mixed H∞ and passivity control for a class of stochastic nonlinear systems with aperiodic sampling. The system states are unavailable and the measurement is corrupted by noise. We introduce an impulsive observer-based controller, which makes the closed-loop system a stochastic hybrid system that consists of a stochastic nonlinear system and a stochastic impulsive differential system. A time-varying Lyapunov function approach is presented to determine the asymptotic stability of the corresponding closed-loop system in mean-square sense, and simultaneously guarantee a prescribed mixed H∞ and passivity performance. Further, by using matrix transformation techniques, we show that the desired controller parameters can be obtained by solving a convex optimization problem involving linear matrix inequalities (LMIs). Finally, the effectiveness and applicability of the proposed method in practical systems are demonstrated by the simulation studies of a Chua’s circuit and a single-link flexible joint robot.  相似文献   

6.
A comparison is given of two exact methods for the analysis of nonlinear systems with stochastic input and stochastic parameters: the Taylor-Cauchy Transform method and the Volterra-Wiener Functional method. The final results check with each other. Examples are provided.  相似文献   

7.
This paper studies the problem of continuous gain-scheduled PI tracking control on a class of stochastic nonlinear systems subject to partially known jump probabilities and time-varying delays. First, gradient linearization procedure is used to construct model-based linear stochastic systems in the vicinity of selected operating states. Next, based on stochastic Lyapunov stabilization analysis, sufficient conditions for the existence of a PI tracking control are established for each linear model in terms of linear matrix inequalities. Finally, continuous gain-scheduled approach is employed to design continuous nonlinear PI tracking controllers on the entire nonlinear jump system. Simulation example is given to illustrate the effectiveness of the developed design techniques.  相似文献   

8.
In this paper, sliding mode control for discrete time systems with stochastic noise in their input channel has been discussed. The idea of process control using control charts has influenced this new approach towards dealing with systems with stochastic noise. The new approach approximates the stochastic noise as a bounded uncertainty, similar to having bounds in the control charts for stochastic process control data. For discrete time systems, this results in a bounded stability in probability of the quasi sliding mode, which is referred to as the N-sigma bounded stability. The probability associated with the stability notions is not fixed and the control engineer may desire lower or higher degrees of stability in terms of this probability. Thus one has design flexibility while implementing the theory in practice, where one might have to adjust the desired degree of stability due to hardware limitations.  相似文献   

9.
In this paper, the global asymptotic stability in probability and the exponential stability in mth moment are investigated for random nonlinear systems with stochastic impulses, whose occurrence is determined by a Poisson process. The stochastic disturbances in the impulsive random nonlinear systems are driven by second-order processes, which have bounded mean power. Firstly, the improved Lyapunov approaches for the global asymptotic stability in probability and the exponential stability in mth moment are established for impulsive random nonlinear systems based on the uniformly asymptotically stable function. Secondly, the improved results are further extended to the impulsive random nonlinear systems with Markovian switching. Finally, two examples are provided to verify the feasibility and effectiveness of the obtained results.  相似文献   

10.
In this paper, the state estimation problem is studied for a class of discrete-time stochastic complex networks with switched topology. In the network under consideration, we assume that measurement outputs can be got from only partial nodes, besides, the switching rule of this network is characterized by a sequence of Bernoulli random variables. The aim of the presented estimation problem is to develop a recursive estimator based on the framework of extended Kalman filter (EKF), such that the upper bound for the filtering error convariance is optimized. In order to address the nonlinear functions, the Taylor series expansion is utilized and the high-order terms of linearization errors are expressed in an exact way. Furthermore, by solving two Ricatti-like difference equations, the gain matrix can be acquired at each time instant. It is shown that the filtering error is bounded in mean square under some conditions with the aid of stochastic analysis techniques. A numerical example is given to demonstrate the validity of the proposed estimator.  相似文献   

11.
This paper discusses the parameter estimation for a class of bilinear-in-parameter systems with colored noise. By utilizing the filtering technique, we derive the relationship between the filtered output and the measurement output and obtain two linear regressive sub-models. A filtering based multi-innovation stochastic gradient algorithm is derived for interactively identifying each sub-model. The proposed algorithm avoids the estimation of correlated noise and improves the parameter estimation accuracy by making full use of the measurement data. The numerical simulation results indicate that the proposed algorithm has higher estimation accuracy than the hierarchical multi-innovation stochastic gradient algorithm.  相似文献   

12.
This paper addresses an active fault diagnosis problem for a class of discrete-time closed-loop system with stochastic noise. By introducing the theories of system identification, a novel active fault diagnosis method is developed to detect and isolate the faults. An important advantage of the proposed method is that there is no need to cut off the original input signal, which is necessary in most active fault diagnosis methods. Firstly, due to the features of the faults, we transform the problem of fault diagnosis into a problem of model selection by estimating model parameters. Then, the sufficient condition for active fault diagnosability is analysed, and the property that auxiliary input signal can enhance the fault diagnosability is given. Finally, simulation studies are carried out to demonstrate the effectiveness and applicability of the proposed method.  相似文献   

13.
This paper studies the finite-time stability and stabilization of linear discrete time-varying stochastic systems with multiplicative noise. Firstly, necessary and sufficient conditions for the finite-time stability are presented via a state transition matrix approach. Secondly, this paper also develops the Lyapunov function method to study the finite-time stability and stabilization of discrete time-varying stochastic systems based on matrix inequalities and linear matrix inequalities (LMIs) so as to Matlab LMI Toolbox can be used.The state transition matrix-based approach to study the finite-time stability of linear discrete time-varying stochastic systems is novel, and its advantage is that the state transition matrix can make full use of the system parameter informations, which can lead to less conservative results. We also use the Lyapunov function method to discuss the finite-time stability and stabilization, which is convenient to be used in practical computations. Finally, three numerical examples are given to illustrate the effectiveness of the proposed results.  相似文献   

14.
This paper mainly studies the stabilization of differently structured highly nonlinear hybrid neutral stochastic systems by delay feedback control. Based on the existing works, our new neutral type stochastic system has completely different highly nonlinear structures in switching subspaces, which is more general and applicable. When such a system is given unstable, we focus on studying the asymptotic and exponential stability criteria by designing a feedback control with a time delay for the underlying system. A simulating example is shown to illustrate the feasibility of these results.  相似文献   

15.
This paper is concerned with the stability analysis problem for a class of delayed stochastic recurrent neural networks with both discrete and distributed time-varying delays. By constructing a suitable Lyapunov–Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions to ensure the global, robust asymptotic stability for the addressed system in the mean square. The conditions obtained here are expressed in terms of LMIs whose feasibility can be checked easily by MATLAB LMI Control toolbox. In addition, two numerical examples with comparative results are given to justify the obtained stability results.  相似文献   

16.
This paper considers the mean-square pinning control problem of fractional stochastic discrete-time complex networks. First, a new fractional stochastic discrete-time complex networks model with stochastic noise is established. Then, some pinning controllers and sufficient conditions are developed for the complex networks. By adopting Lyapunov energy function theory and matrix analysis theory, it proved that the synchronization of the fractional stochastic discrete-time complex networks can be achieved in a mean-square sense via pinning control. In addition, these results are extended to solve the synchronization problem of general fractional discrete-time complex networks without noise. Finally, several numerical examples are given to verify the correctness of the obtained theoretical results.  相似文献   

17.
In complex networks, asymptotic properties play an important role in modeling, analysis and design in both aspects of theory and practice. In this paper, our focus is on exponential synchronization for a class of complex networks. Under certain conditions, a feedback control and stochastic periodically intermittent noise are designed to synchronize the networks. Such synchronization scheme needs less control energy due to the usage of the intermittent noise. The threshold of intermittent rate for synchronization scheme is derived. Moreover, the noise states are observed in discrete-time mode, which reduces the complexity and the computation burden for continuous observations. The observation supremum is obtained by solving a transcendental equation. Finally, a simulation example is provided, and the comparison results with some existing methods illustrate the effectiveness and advantages of the proposed new design strategy.  相似文献   

18.
In this paper, based on Stirling’?s polynomial interpolation formula, the Second-order Central Difference Predictive Filter (CDPF2) is proposed for nonlinear estimation. To facilitate the new method, the algorithm flow of CDPF2 is given first. Then, the theoretical deductions demonstrate that the estimated accuracy of the model error and system state for the CDPF2 is higher than that of the conventional PF. In addition, the stochastic boundedness and the error behavior of CDPF2 is analyzed for general nonlinear systems in a stochastic framework. The theoretical analysis presents that the estimation error will remain bounded and the covariance will remain stable if the system?s initial estimation error, disturbing noise terms and model error are small enough, which is the core part of the CDPF2 theory. All of the results have been demonstrated by numerical simulations for a nonlinear example system.  相似文献   

19.
This paper is dedicated to the stochastic bipartite consensus issue of discrete-time multi-agent systems subject to additive/multiplicative noise over antagonistic network, where a stochastic approximation time-varying gain is utilized for noise attenuation. The antagonistic information is characterized by a signed graph. We first show that the semi-decomposition approach, combining with Martingale convergence theorem, suffices to assure the bipartite consensus of the agents that are disturbed by additive noise. For multiplicative noise, we turn to the tool from Lyapunov-based technique to guarantee the boundedness of agents’ states. Based on it, the bipartite consensus with multiplicative noise can be achieved. It is found that the constant stochastic approximation control gain is inapplicable for the bipartite consensus with multiplicative noise. Moreover, the convergence rate of stochastic MASs with communication noise and antagonistic exchange is explicitly characterized, which has a close relationship with the stochastic approximation gain. Finally, we verify the obtained theoretical results via a numerical example.  相似文献   

20.
This paper is devoted to the adaptive finite-time control for a class of stochastic nonlinear systems driven by the noise of covariance. The traditional growth conditions assumed on the drift and diffusion terms are removed through a technical lemma, and the negative effect generated by unknown covariance noise is compensated by combining adaptive control technique with backstepping recursive design. Then, without imposing any growth assumptions, a smooth adaptive state-feedback controller is skillfully designed and analyzed with the help of the adding a power integrator method and stochastic backstepping technique. Distinctive from the global stability in probability or asymptotic stability in probability obtained in related work, the proposed design algorithm can guarantee the solution of the closed-loop system to be finite-time stable in probability. Finally, a stochastic simple pendulum system is skillfully constructed to demonstrate the effectiveness of the proposed control scheme.  相似文献   

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