time delay

摘要： In this paper, an optimization model is proposed to simulate and predict the current situation of smog. The model takes the interval grey number sequence with the known possibility function as the original data, and constructs a time-delay nonlinear multivariable grey model MGM based on the new kernel and degree of greyness sequences considering its time-delay and nonlinearity. The time-delay parameter is determined by the maximum value of the grey time-delay absolute correlation degree, and the nonlinear parameter is determined by the minimum value of average relative error. In order to verify the feasibility of the model, this paper uses the smog related data of Nanjing city for simulation and prediction. Compared with the other four models, the new model has higher simulation and prediction accuracy.

摘要： With the rapid development of data applications in the scene of Industrial Internet of Things(IIoT),how to schedule resources in IIoT environment has become an urgent problem to be solved.Due to benefit of its strong scalability and compatibility,Kubernetes has been applied to resource scheduling in IIoT scenarios.However,the limited types of resources,the default scheduling scoring strategy,and the lack of delay control module limit its resource scheduling performance.To address these problems,this paper proposes a multi-resource scheduling(MRS)scheme of Kubernetes for IIoT.The MRS scheme dynamically balances resource utilization by taking both requirements of tasks and the current system state into consideration.Furthermore,the experiments demonstrate the effectiveness of the MRS scheme in terms of delay control and resource utilization.

摘要： Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

摘要： An approach for joint direction of arrival(DOA) angle and frequency estimation for a linear array is investigated in this paper. Specifically, we make the utmost of the autocorrelation and cross-correlation information to propose an extended DOAmatrix(EDOAM) method. Subsequently, we obtain the autopaired angle and frequency estimates by the eigenvalues and the corresponding eigenvectors of the novel DOA matrix. Furthermore, the proposed method surpasses the DOA-matrix method which partly ignores the autocorrelation and cross-correlation information. Finally, the proposed method works well for both uniform and non-uniform linear arrays. The simulation consequences indicate the superiority of our proposed approach.

摘要： The finite-time stability and the finite-time contractive stability of solutions for nonlinear fractional differential equations with bounded delay are investigated. The derivative of Lyapunov function along solutions of the considered system is defined in terms of the Caputo fractional Dini derivative. Based on the Lyapunov-Razumikhin method, several sufficient criteria are established to guarantee the finite-time stability and the finite-time contractive stability of solutions for the related systems. An example is provided to illustrate the effectiveness of the obtained results.

摘要： The existence of time delay in complex industrial processes or dynamical systems is a common phenomenon and is a difficult problem to deal with in industrial control systems,as well as in the textile field.Accurate identification of the time delay can greatly improve the efficiency of the design of industrial process control systems.The time delay identification methods based on mathematical modeling require prior knowledge of the structural information of the model,especially for nonlinear systems.The neural network-based identification method can predict the time delay of the system,but cannot accurately obtain the specific parameters of the time delay.Benefit from the interpretability of machine learning,a novel method for delay identification based on an interpretable regression decision tree is proposed.Utilizing the self-explanatory analysis of the decision tree model,the parameters with the highest feature importance are obtained to identify the time delay of the system.Excellent results are gained by the simulation data of linear and nonlinear control systems,and the time delay of the systems can be accurately identified.

摘要： In this paper,we developed a stability analysis for discrete-time uncertain time-delay systems governed by an infinite-state Markov chain(DUTSs-IMC).Some sufficient conditions for the considered systems to be exponential stability in mean square with conditioning(ESMS-C)are derived via linear matrix inequalities(LMIs),which can be examined conveniently.Under novel sufficient conditions,the equivalence among asymptotical stability in mean square(ASMS),stochastic stability(SS),exponential stability in mean square(ESMS),and ESMS-C has been established.Besides,numerical simulations are employed in result validation.

摘要： In this paper,a tristable viscoelastic isolation system with stochastic excitation under both displacement and velocity delayed feedback control is considered.Firstly,the theoretical expressions of the mean first-passage time(MFPT)to measure the activated escape between different potential wells are derived.Induced nonlinear transition dynamics due to the noise and time delays are mainly discussed.It is found that the delay-induced behaviours affect the transitions between the equilibrium points of the system,the corresponding phenomenon of the delay-enhanced stability is observed.In this respect,the existence of the maxima of the MFPT1 and the MFPT2 is found in one period.Meanwhile,the MFPT1 and the MFPT2 show the monotonic behaviour with the increase of the noise intensity.Additionally,the stationary probability density of the amplitude and the stationary mean amplitude are derived.The influence regimes of the system parameters on both stationary probability density of the amplitude and the stationary mean amplitude are explored.This paper establishes the relationship between system parameters and dynamical properties of the tristable viscoelastic isolation system.This provides a fundamental guidance for the optimization of the viscoelastic isolation by utilizing the technique of delayed feedback control.

摘要： Command governor–based adaptive control(CGAC)is a recent control strategy that has been explored as a possible candidate for the challenging task of precise maneuvering of unmanned underwater vehicles(UUVs)with parameter variations.CGAC is derived from standard model reference adaptive control(MRAC)by adding a command governor that guarantees acceptable transient performance without compromising stability and a command filter that improves the robustness against noise and time delay.Although simulation and experimental studies have shown substantial overall performance improvements of CGAC over MRAC for UUVs,it has also shown that the command filter leads to a marked reduction in initial tracking performance of CGAC.As a solution,this paper proposes the replacement of the command filter by a weight filter to improve the initial tracking performance without compromising robustness and the addition of a closed-loop state predictor to further improve the overall tracking performance.The new modified CGAC(M-CGAC)has been experimentally validated and the results indicate that it successfully mitigates the initial tracking performance reduction,significantly improves the overall tracking performance,uses less control force,and increases the robustness to noise and time delay.Thus,M-CGAC is a viable adaptive control algorithm for current and future UUV applications.

摘要： This paper is devoted to the problem of stabilizing a Hopfield-type neural network with bi-directional ring architecture and two delays. The delay-independent and delay-dependent stability conditions are explicitly presented by the method of the characteristic roots and the skill of mathematical analysis. Moreover, if a link between the adjacent two neurons is cut, the ring neural network turns to a linear one, and the stability results are also established. Furthermore, a comparative analysis for the ring and linear network shows that the stability domain is enlarged after the breaking.