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This article solves the problem of almost sure exponential stabilization via output feedback control for stochastic feedforward nonlinear systems with the unknown growth rate. A novel dynamic gain is introduced not only to cope with system uncertainties but also to ensure exponential convergence. Based on this dynamic gain, an adaptive output feedback controller is explicitly constructed. By introducing an improved stochastic analysis method, we rigorously prove that the closed-loop system has an almost surely unique solution, all the closed-loop signals are bounded almost surely, and the solution of the closed-loop system tends to the equilibrium position exponentially fast.

In this article, we study the adaptive stability for parabolic partial differential equation (PDE)-ordinary differential equation (ODE) cascade systems with actuator dynamics, where the actuator dynamics are nonlinear subject to unknown parameters. Compared with a class of PDE–ODE coupled systems that the control input only acts on the PDE boundary and the linear sandwiched system without uncertainty, the structure of such systems is more complex. First of all, infinite-dimensional backstepping transformation is adopted. The original PDE-ODE cascade system is changed to a new system that is easier to design. On this basis, finite-dimensional backstepping transformation and adaptive compensation technology are combined to develop a state-feedback controller. Then, the boundedness of all the signals in the closed-loop system is proved by the Lyapunov functional analysis. Furthermore, the control law and the original system states eventually converge to zero. Finally, different simulation data are presented to illustrate the validity of the theoretical results.

Dear Editor, This letter deals with the output feedback stabilization of a class of high-order nonlinear time-delay systems with more general low-order and high-order nonlinearities. By constructing reduced-order observer, based on homogeneous domination theory together with the adding a power integrator method, an output feedback controller is developed to guarantee the equilibrium of the closed system globally uniformly asymptotically stable.

Accumulating evidences show that circular RNAs (circRNAs) play an important role in regulating gene expression, and involve in many complex human diseases. Identifying associations of circRNA with disease helps to understand the pathogenesis, treatment and diagnosis of complex diseases. Since inferring circRNA-disease associations by biological experiments is costly and time-consuming, there is an urgently need to develop a computational model to identify the association between them. In this paper, we proposed a novel method named KNN-NMF, which combines $K\ $Knearest neighbors with nonnegative matrix factorization to infer associations between circRNA and disease (KNN-NMF). Frist, we compute the Gaussian Interaction Profile (GIP) kernel similarity of circRNA and disease, the semantic similarity of disease, respectively. Then, the circRNA-disease new interaction profiles are established using weight $K$K nearest neighbors to reduce the false negative association impact on prediction performance. Finally, Nonnegative Matrix Factorization is implemented to predict associations of circRNA with disease. The experiment results indicate that the prediction performance of KNN-NMF outperforms the competing methods under five-fold cross-validation. Moreover, case studies of two common diseases further show that KNN-NMF can identify potential circRNA-disease associations effectively.

Motivated by the thermoelastic coupling effect arising in microelectromechanical systems (MEMS), event-triggered control of second-order ODE-heat systems coupled at intermediate point is investigated. The event-triggered control includes two parts, one is the feedback control signal, and the other is the event-triggered mechanism that decides when to update the control input. First, we design an event-triggered controller by using Zero-Order Hold to a continuous-time controller. Then, a dynamic triggering condition is established. Next, we derive that the existence of a minimal dwell-time, which avoids the occurrence of Zeno behavior. By utilizing Lyapunov-Krasovskii functional method, the global exponential stability of the closed-loop system is demonstrated. Finally, the simulation data based on the thermoelastic coupling system is displayed to demonstrate the availability of the theoretical results.

This article investigates the problem of global neural network (NN) tracking control for uncertain nonlinear systems in output feedback form under disturbances with unknown bounds. Compared with the existing NN control method, the differences of the proposed scheme are as follows. The designed actual controller consists of an NN controller working in the approximate domain and a robust controller working outside the approximate domain, in addition, a new smooth switching function is designed to achieve the smooth switching between the two controllers, in order to ensure the globally uniformly ultimately bounded of all closed-loop signals. The Lyapunov analysis method is used to strictly prove the global stability under the combined action of unmeasured states and system uncertainties, and the output tracking error is guaranteed to converge to an arbitrarily small neighborhood through a reasonable selection of design parameters. A numerical example and a practical example were put forward to verify the effectiveness of the control strategy.

This article investigates adaptive state-feedback stabilization problem for a class of stochastic high-order nonlinear systems with unknown time-varying powers and stochastic inverse dynamics for the first time. The existence of stochastic inverse dynamics, unknown parameters, and time-varying powers makes stochastic high-order nonlinear systems essentially different from the related papers, which brings a series of obstacles to achieve the control objective. By virtue of the parameter separation principle, adaptive technique and some flexible algebraic methods, a novel adaptive state-feedback controller is designed to guarantee that the equilibrium of the closed-loop system is globally stable in probability. Finally, a simulation is provided to demonstrate the effectiveness of the control scheme. [ABSTRACT FROM AUTHOR]

We propose an approach which is different from the usual Lyapunov-Krasovskii function method to analyze asymptotic stability of nonlinear time-varying systems with bounded and unbounded delays. For the case of unbounded delay, new delay-independent criteria are provided when the involved nonlinear terms satisfy linear and nonlinear growth conditions. For the case of bounded delay, we establish a new delay-dependent criterion based on a model transformation. Numerical examples are given to demonstrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of adaptive neural output-feedback decentralized control for a class of strongly interconnected nonlinear systems suffering stochastic disturbances. An state observer is designed to approximate the unmeasurable state signals. Using the approximation capability of radial basis function neural networks (NNs) and employing classic adaptive control strategy, an observer-based adaptive backstepping decentralized controller is developed. In the control design process, NNs are applied to model the uncertain nonlinear functions, and adaptive control and backstepping are combined to construct the controller. The developed control scheme can guarantee that all signals in the closed-loop systems are semiglobally uniformly ultimately bounded in fourth-moment. The simulation results demonstrate the effectiveness of the presented control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates state feedback stabilization problem of a class of stochastic cascade nonlinear time-delay systems with stochastic inverse dynamics. By characterizing unmeasured stochastic inverse dynamics with stochastic input-to-state stability condition, without imposing any growth condition on time-delay system nonlinearities, a delay-independent, dynamic state feedback controller is constructed. It is shown that the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability. [ABSTRACT FROM AUTHOR]

This paper aims to solve the finite-time stabilization problem for stochastic high-order nonlinear systems with stochastic inverse dynamics. By characterizing unmeasured stochastic inverse dynamics with finite-time stochastic input-to-state stability (FT-SISS), borrowing from some ideas of the Lyapunov function, sign function, backstepping and FT-SISS methods, and using stochastic finite-time stability theory, a new design and analysis method is given to guarantee global finite-time stability in probability of the closed-loop stochastic systems. [ABSTRACT FROM AUTHOR]

This paper discusses adaptive control problems of high-order stochastic nonlinear time-delay systems. Compared with the existing results, the considered system involves uncertain parameters, intricate stochastic drift terms, and unknown time-varying delays. Based on a modified method of adding a power integrator and Lyapunov–Krasoviskii functional technique, new controllers are successfully constructed to achieve the objectives of adaptive stabilization and adaptive tracking, respectively. Examples are given to show the effectiveness of the proposed control strategies. [ABSTRACT FROM AUTHOR]

In this note, we study the stabilization problem of positive switched linear system (PSLS) with disturbance. By introducing a class of weak common linear copositive Lyapunov functions, we design time-dependent switching rules under which the system is asymptotically stable. Both continuous-time and discrete-time PSLS are taken into consideration, and the obtained results are also extended to nonpositive switched systems. Finally, the theoretical results are applied to consensus problem of multiagent systems with switching topologies and disturbance. [ABSTRACT FROM PUBLISHER]

This paper studies the global stabilization problem for a class of high-order nonlinear systems with low-order and high-order nonlinearities, and multiple time-varying delays. Systems become more general due to both low-order and high-order in nonlinearities taking values in certain intervals. By introducing a novel Lyapunov–Krasovskii functional, a state feedback controller based on the Lyapunov–Krasviskii theorem together with the adding a power integrator and sign function methods is designed to guarantee the globally uniformly asymptotic stability of the closed-loop system. [ABSTRACT FROM AUTHOR]

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

For a class of stochastic high-order nonlinear systems, by introducing the combined homogeneous domination and sign function design approach, this technical note solves the problem of output-feedback control under the weaker high-order and nonlinear growth conditions. [ABSTRACT FROM AUTHOR]

Aiming at some boiler tubescrack in a power plant, the element composition and the valence of elements in corrosion products on the outer surfaces of the boiler tubes were analysed by Scanning Electron Microanalyzer (SEM) and X-ray Photoelectron Spectroscopy (XPS), and the corrosion reason and mechanism of the outer surfaces of the boiler tubes were studied.The results showed as follows. (1)The content of element S in the corrosion products on the outer surfaces of the fire side boiler tubes was bigger than that in the corrosion products on the outer surfaces of the back side boiler tubes and the corrosion of the outer surfaces of the fire side boiler tubes was more serious than that of the outer surfaces of the back side boiler tubes. (2) the element S in the corrosion products existed in the form of sulfate (SO42-), because the valence of S in the corrosion products on the outer surfaces of the fire side boiler tubes and the back side boiler tubes was +6, not-2. (3) the element Fe in the corrosion products on the outer surfaces of the fire side boiler tubes and the back side boiler tubes existed in the form of Fe3O4, Fe2O3 or Fe2(SO4)3. (4) The corrosion of the boiler tubes was induced by sulphate under high temperature, and aggravated with the temperature of the outer surfaces of the boiler tubes elevated.

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. [ABSTRACT FROM AUTHOR]

This technical note further investigates more general stochastic nonlinear systems with stochastic integral input-to-state stability (SiISS) inverse dynamics and focuses on solving the following problems: 1) a class of counterexamples which are different from that in refid="ref14"/ are reconstructed to discuss the relationship between two small-gain type conditions on SiISS and 2) under the weaker conditions on nonlinearities, based on a reduced-order observer, small-gain type condition on SiISS and stochastic LaSalle theorem, an output feedback controller is constructed to guarantee the global asymptotical stability in probability of the closed-loop stochastic system. [ABSTRACT FROM AUTHOR]

The definition and the sources of the particulate pollutant in the transformer oil were described in the article. The prevention and elimination of the particulate pollutant were introduced as well.

This technical note considers a class of high-order stochastic nonlinear systems with stochastic integral input-to-state stability (SiISS) inverse dynamics, and drift and diffusion terms depending upon the stochastic inverse dynamics and all the states. A new design and analysis approach to the problem of state-feedback global regulation is developed to guarantee that all the signals of the closed-loop system are bounded almost surely and the states can be regulated to zero almost surely. [ABSTRACT FROM AUTHOR]

The mechanism of oil flow electrification in transformers was described in this paper. The mechanism of oil flow electrification in transformers could be understood from the effect of the oil flow’s movement and the electromotive action of AC electric field. The electric polarity of oil flow and the insulating layer were mainly depended on the state of charged cations and anions in oil, while the surface characteristics of solid materials only played a supporting adsorption role.

For a class of stochastic nonlinear systems in which the drift and diffusion vector fields depend on the unmeasurable states besides the measurable output, the research purpose of this technical note is to find the maximum value interval of observer gain for the desired control performance. For this interval, the designed output-feedback controller ensures that the equilibrium at the origin is globally asymptotically stable in probability, and the inverse optimal stabilization in probability is achieved. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of observer-based decentralized control for a class of large-scale stochastic high-order feedforward systems with multi time delays. By using the homogeneous domination idea and constructing the implementable observer, the decentralized output-feedback controller design scheme is firstly proposed. Then, with the aid of stochastic time delay system stability theory, the globally asymptotically stable in probability of the closed-loop system is verified by selecting an appropriate Lyapunov–Krasoviskii functional. Finally, an example is provided to demonstrate the efficiency of the proposed design method. [ABSTRACT FROM AUTHOR]

Abstract This paper deals with the problem of state bounding for a class of nonlinear time-varying systems with delay and bounded disturbance. By using a model transformation and an approach developed in positive systems, new delay-dependent explicit conditions have been established to guarantee all the state trajectories of the system converge exponentially within a ball. Two illustrative examples are given to show that the obtained results can be applied to some cases not covered by preceding results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the problem of output feedback stabilization for high-order nonlinear systems with more general low-order and high-order nonlinearities multiplied by a polynomial-type output-dependent growth rate is studied. By constructing the novel Lyapunov function and observer, based on the homogeneous domination and adding a power integrator methods, an output feedback controller is developed to guarantee that the equilibrium of the closed-loop system is globally uniformly asymptotically stable. [ABSTRACT FROM AUTHOR]

This paper investigates the consensus problem for third-order discrete-time multi-agent systems in directed networks. For the case when each agent can only receive the information of position and velocity from its neighbors, necessary and sufficient conditions for consensus have been proposed. In contrast to the preceding work, we not only present the exact consensus value, but also illustrate the influence of scaling parameters and nonzero eigenvalues of the involved Laplacian matrix on consensus. Two numerical examples are given to demonstrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

We study the input-to-state stability (ISS) of switched nonlinear input delay systems under asynchronous switching. Our results apply to cases where some subsystems of the switched systems are not necessarily stable under the influence of input delay. By making a compromise among the matched-stable period, the matched-unstable period, and the unmatched period and allowing the increase of the Lyapunov–Krasovskii functional (LKF) on all the switching times, the extended stability criteria for switched delay systems in generally nonlinear setting are derived first. Then, we focus on switched nonlinear input delay systems where the presence of the input delay leads to the instability of some subsystems of it. By explicitly constructing input-to-state stable LKF, the sufficient conditions for ISS of switched nonlinear input delay systems under asynchronous switching are presented. Finally, two examples are given to illustrate the effectiveness of the proposed theory. [ABSTRACT FROM AUTHOR]