查看更多>>摘要：In this paper, a fast algorithm is proposed for solving distributed-order time-space fractional diffusion equations. Integral terms in time and space directions are discretized by the Gauss-Legendre quadrature formula. The Caputo fractional derivatives are approximated by the exponential-sum-approximation method, and the finite difference method is applied for spatial approximation. The coefficient matrix of the discretized linear system is symmetric positive definite and possesses block-Toeplitz-Toeplitz-block structure. The preconditioned conjugate gradient method with a block-circulant-circulant-block pre conditioner is employed to solve the linear system. Theoretically, the stability and convergence of the proposed scheme are discussed. Numerical experiments are carried out to demonstrate the effectiveness of the scheme.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：The probabilistic reachability problem, which involves the computation of probabilistic reachable sets, is studied for nondeterministic systems. In the existing works, the system evolution initialized from the probabilistic reachable set is required to reach the target set with a certain probability in a given time horizon. In this paper, the definition of probabilistic reachable sets is refined by taking into account time-varying target set and obstacle. In the context of this definition, the evolution of the system is required not only to reach the target set but also to avoid obstacle. We address two distinct interpretations of probabilistic reachability problem via dynamic planning. In the first case, the control policy is given. In the second case, the control policy is a parameter to be optimized. A numerical method is proposed to compute probabilistic reachable sets. First, a scalar function in the state space is constructed by backward recursion and grid interpolation, and then the probabilistic reachable set is represented as a nonzero upper level set of this scalar function. In addition, based on the constructed scalar function, the optimal control policy can be designed. Two examples are provided at the end of this article. The first example consists of a one-dimensional problem where the analytical solution is compared with the results of the proposed method in order to analyze the computational accuracy. The second example, which contains a three-dimensional problem, is used to demonstrate the effectiveness of the proposed method. (c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：In the random hypersurface model for extended target tracking problem, the scaling factor in the measurement equation brings difficulty for existing particle filter to calculate the likelihood in the weighting update stage. In this paper, we firstly simplify the existing approximate likelihood function where the distribution of the scaling factor is approximated by Gaussian one. Then, by directly dealing with the distribution of the scaling factor whose square has uniform distribution, we propose a novel explicit formula of the logarithm of likelihood. Based on this formula, a feasible weighting scheme is obtained and a novel particle filtering algorithm (NPFA) is proposed. Simulation shows that NPFA improves estimation accuracy compared with the existing unscented Kalman filter and particle filter for the tracking problem under discussion.(c) 2022 Published by Elsevier Inc.
查看更多>>摘要：In this paper, we consider optimal control of nonlinear fractional-order systems with multiple pantograph-delays, where the fractional-order derivatives are expressed in the Caputo sense. For this problem, we first propose an explicit integration scheme to numerically solve the nonlinear fractional-order system with multiple pantograph-delays and approximate the cost functional using the trapezoidal rule. This yields a series of nonlinear parameter optimization problems. Then, we derive gradients of the cost functions in the resulting problems. Furthermore, we present a gradient-based optimization approach to solve the fractional pantograph-delay optimal control problem. Finally, we validate the proposed solution approach by solving three numerical examples.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：The direct current(DC) multi-microgrid(MMG) with island operation mode is a system formed by interconnecting DC multiple microgrids, which is more complicated than a single microgrid. First of all, this paper proposes the modeling method of the power regulation cost for each controllable unit to guide their power regulation order, which reduces the power regulation cost. Second, the hierarchical control strategy is proposed. The toplevel control allocates power through the consensus algorithm to accelerate the convergence rate of the state of charge(SoC) of energy storage batteries(ESBs). The convergence of SoC reduces the switching times of working mode of MMG system caused by the deviation of SoC from the normal working range, which further reduces the cost of power regulation. The bottom-level control performs constant power control on each controllable unit according to the load rate of ESB obtained by top-level control. Furthermore, the correction scheme of measured SoC value is proposed according to its predicted value when the measured SoC value of ESB is inaccurate, which ensures the stability of MMG system. Finally, the example simulation shows that the consensus algorithm can effectively solve the real-time power distribution problem of MMG.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：In this article, the synchronization issue of memristive neural networks (MNNs) under denial-of-service (DoS) attacks and actuator saturation is investigated via an observer based controller. Due to actual physical constraint, the effect of actuator saturation is taken into account in the controller design. Unlike the existing works where the communication environment is secure, DoS attacks are explored in the communication channel connecting master and slave MNNs. Based on the above considerations, an observer-based control approach is developed to estimate the MNNs states and guarantee the MNNs synchronization in the presences of DoS attacks and actuator saturation. By using the Lyapunov method and stochastic analysis technique, the sufficient synchronization conditions are derived via a set of linear matrix inequalities (LMIs). Meanwhile, the attraction domain of error system is estimated to satisfy the demand of actuator saturation. Then, numerical simulation is used to manifest the validity of our theoretical results. Finally, the proposed synchronization theory is applied to image encryption. The experimental results demonstrate that the presented image encryption scheme has a reliable performance.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：In this paper, the issue of event-triggered it-state estimation is addressed for a class of Markovian jumping neural networks (MJNNs) with mixed delays. The mixed delays involve both the infinitely distributed delay and the time-varying delay without requiring the upper bound, which has a distinction in existing conclusions and makes the model be more comprehensive. An event-triggered mechanism (ETM) with mode dependence is adopted to determine the appropriate updating instants of measurement outputs so as to alleviate the transmission of signals. By constructing a novel time-varying L-K functional with a general convergency rate and employing several analysis techniques, a sufficient criterion is obtained for ensuring the stochastic it-stability performance of error system, which is a more general stability performance including exponential stability, power stability as well as logarithmic stability as its special cases. Finally, three numerical examples are listed to demonstrate the effectiveness of the proposed method.(C) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：Research on the estimation of unknown parameters in uncertain differential equations has been a concerned subject for scholars in recent years. For this reason, some scholars have proposed many methods to estimate the unknown parameters. However, these unknown parameters are constants. This paper considers estimation methods for time-varying pa-rameters, the least squares estimation method is rewritten. Firstly, estimates of a set of time-varying parameters are obtained. Secondly, the fit function for this set of estimates, which is obtained by means of a regression fit is considered to be a time-varying param-eter. Meanwhile, the criteria is given to determine whether the fit function is reasonable. Finally, two numerical examples of uncertain differential equations are presented to verify the feasibility of the above method.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：In this paper, finite-time stabilization (FTS) issue of delayed quaternion-valued coupled neural networks (DQVCNNs) with saturated impulse is discussed for the first time. Satu-rated impulse, time-varying delay and quaternion are first considered into coupled neural networks (CNNs), which makes the model more complex and realistic. Secondly, a hybrid feedback controller is designed, some conditions are derived to stabilize DQVCNNs with saturated impulse in finite time by the idea of polytopic representation and sector non-linearity model, respectively. Furthermore, this paper shows the settling-time of DQVCNNs with saturated impulse, which discloses it related to both impulse and initial state. Next, this paper also presents several corresponding essential corollaries. Lastly, the feasibility of the derived results is further explained by two examples. (c) 2022 Elsevier Inc. All rights reserved.
NSTL
Elsevier