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In this paper, a new improved smoothing Newton algorithm for the nonlinear complementarity problem was proposed. This method has two-fold advantages. First, compared with the classical smoothing Newton method, our proposed method needn’t nonsingular of the smoothing approximation function; second, the method also inherits the advantage of the classical smoothing Newton method, it only needs to solve one linear system of equations at each iteration. Without the need of strict complementarity conditions and the assumption of P0 property, we get the global and local quadratic convergence properties of the proposed method. Numerical experiments show that the efficiency of the proposed method.

In this paper, we propose a new high-order total variation regularized model with box constraint for image compressive sensing reconstruction. Because of the separable structure of this model, we can easily decompose into three subproblems by splitting the augmented Lagrangian function. To effectively solve the proposed new model, a fast alternating minimization method with accelerated technique is presented. Moreover, the proposed method applies a linearized strategy for quadratic terms to get the closed-form solution and reduce the computation cost. Numerical experiments show that our proposed model can get better performance than several current state-of-the-art methods in terms of signal to noise ratio (SNR) and visual perception.

For the problems of power fluctuation and over-current in grid-connected inverters under unbalanced grid voltage, a fault ride through control strategy based on finite control set-model predictive control (FCS-MPC) with peak current limitation is proposed for fault-tolerant NPC three-level photovoltaic grid-connected inverter. Firstly, the current reference value is calculated with the goal of balancing the current, eliminating active and reactive power oscillations. Then, the quantitative relationship between the power reference set value and the peak output current value is deduced to guide the power reference value setting under unbalanced grid voltage. In addition, the grid-connected model predictive current control strategy based on the reference voltage cost function method is used to realize the accurate tracking of the reference current. Simulation results show that the proposed method can realize the control objectives of output current balance, active power constant, and reactive power constant under unbalanced grid voltage, and the current peak is limited effectively under the three control objectives.

Total variation regularization is well-known for recovering sharp edges; however, it usually produces staircase artifacts. In this paper, in order to overcome the shortcoming of total variation regularization, we propose a new variational model combining high-order total variation regularization and l1 regularization. The new model has separable structure which enables us to solve the involved subproblems more efficiently. We propose a fast alternating method by employing the fast iterative shrinkage-thresholding algorithm (FISTA) and the alternating direction method of multipliers (ADMM). Compared with some current state-of-the-art methods, numerical experiments show that our proposed model can significantly improve the quality of restored images and obtain higher SNR and SSIM values.

Ion exchange is an effect process for removing of heavy metals from wastewater effluents. In the present study, the sorption of nickel ion (Ni (Π)) in effluent from wastewater treatment plant of automobile industry was studied by using D113 ion exchange resin. The static shaking absorption experiments revealed that the process of absorption of Ni (Π) was more in line with non-monolayer absorption model of Freundlich that with a maximum absorption capacity of 36.13 mg/g. The column experimental data showed that under the optimum operating conditions which was pH 7.0, temperature 30 °C and 20 mL/min of flow rate it could meet the emission standard (GB25467-2010) of China with 10 h of processing time. Desorption rate of D113 resin could reach above 93.6% by using 0.8% H2SO4 with 5 mL/min of flow rate, and the analysis of FT-IR and SEM proved that −OH was the main functional group of the resin participate in metal binding, which demonstrated that the D113 resin could be considered as an effectively way for the advanced treatment of Ni (Π) ions in the effluents of automobile industry wastewaters.

Communication Based Train Control System (CBTC) has become the development trend of train control system, and generating safe and reasonable movement authority is the key to ensure the normal operation of the whole system. Combined with the security of the system, a security analysis method based on fault tree information to construct fault Statechart is proposed. The fault tree that generates the abnormality of the movement authority is analyzed, and it is represented as a form that the Statechart can describe, thereby establishing a fault statechart of the movement authority generating abnormality. Finally, the formal modeling of the fault statechart is carried out by using the time automaton theory, and the fault state unreachable is taken as the attribute of the specification for inspection. The results show that the method of combining fault Statechart and time automata proposed in the paper is feasible and suitable for the analysis and verification of safety critical systems.

In order to realize effective prevention from faults, cut-off the fault quickly and power supply recovery from power loss load in intelligent distribution network, this paper proposed a state transition model of self-healing control for intelligent distribution network based on Finite State Machine (FSM). We divided the running states into normal state and fault state, added finite variables to FSM. determined the operation state transition control schemes of intelligent distribution network self-healing control. Considering distributed generation(DG), we established the state transition model of intelligent distribution network self-healing control system on Matlab/Stateflow platform and applied to simulation example. The results show that the proposed state transition scheme is feasible and effective.

Convex total variation (TV) regularization models have been widely used in remote sensing image restoration problems; however, these models tend to produce staircase effects. We consider a nonconvex second-order TV regularization model with linear constraints for remote sensing image restoration. To solve the nonconvex second-order TV regularization model, we propose an efficient alternating minimization algorithm based on generalized iterated shrinkage algorithm and alternating direction method of multipliers. Experimental results demonstrate the effectiveness of the proposed model, which can reduce staircase effects while preserving edges. In terms of signal-to-noise ratio and structural similarity index measure, the experimental results show that our proposed model and algorithm can give better performance compared with some state-of-the-art methods.

Pinning adaptive synchronization is investigated in weighted complex networks and several criteria are obtained for globally exponentially asymptotic synchronization. The number of pinned nodes can be obtained by calculating the eigenvalue of the minor matrix of an extended coupling matrix. Especially, pinning adaptive controllers are rather simple compared with some traditional controllers. Specifically and randomly pinning schemes are considered. When the network Control Rank information is known, the specifically pinning scheme of the most highly connected nodes is shown to require a significantly smaller number of local controllers when compared with the randomly pinning scheme. Finally, numerical simulations are provided to illustrate the effectiveness of the proposed synchronization criteria in weighted dynamical networks.

In this paper, based on the Kanzow-Kleinmichel (KK) function, we introduce a new nonlinear complementarity problem (NCP) function: penalized KK function. We show that the function possesses desirable properties similar to those of the KK function. Based on this new NCP function, we reformulate the NCP to a system of semismooth equations. We also propose a new semismooth Levenberg–Marquardt method to solve the system of semismooth equations that employs both trust region techniques and line searches. The global and quadratic convergence properties can be established under very mild assumptions. Numerical results show the effectiveness of the proposed algorithm and also indicate that superior behaviour of the proposed new NCP function.

In this paper, we introduce a new class of smoothing functions, which include some popular smoothing complementarity functions. We show that the new smoothing functions possess a system of favorite properties. The existence and continuity of a smooth path for solving the nonlinear complementarity problem (NCP) with a P 0 function are discussed. The Jacobian consistency of this class of smoothing functions is analyzed. Based on the new smoothing functions, we investigate a smoothing Newton algorithm for the NCP and discuss its global and local superlinear convergence. Some preliminary numerical results are reported.

In the paper [S.P. Rui and C.X. Xu, A smoothing inexact Newton method for nonlinear complementarity problems, J. Comput. Appl. Math. 233 (2010), pp. 2332–2338], the authors proposed an inexact smoothing Newton method for nonlinear complementarity problems (NCP) with the assumption that F is a uniform P function. In this paper, we present a non-monotone inexact regularized smoothing Newton method for solving the NCP which is based on Fischer–Burmeister smoothing function. We show that the proposed algorithm is globally convergent and has a locally superlinear convergence rate under the weaker condition that F is a P 0 function and the solution of NCP is non-empty and bounded. Numerical results are also reported for the test problems, which show the effectiveness of the proposed algorithm.

Synchronization in classes of continuous-time dynamical unweighted networks with different topologies is investigated. A synchronization-optimal network model based on rewiring of links is proposed. Compared with other networks, it exhibits a stronger synchronizability. We presented link density and investigated the correlation of synchronizability, link density and heterogeneity in degree distribution. In this work, it will be shown that synchronizability of Type I networks is independent of heterogeneity in the degree distribution when the link density is smaller than 0.02. Synchronizability and link density are proportional. When the link density is larger than 0.025, heterogeneity decides the curve slope. The synchronizability of Type II networks is drastically enhanced by enhancing the link density when the link density is smaller than 0.025. However synchronizability increases weakly by enhancing the link density when the link density is larger than 0.025.

Synchronization in classes of continuous-time dynamical networks with different topologies is investigated. A synchronization-optimal algorithm based on the synchronization criterion is proposed so as to get the appropriate topology such that complex network has the optimal synchronizability. It has been argued that heterogeneity suppresses synchronization in unweighted networks. However, it is shown in this work that synchronizability of Type I networks is independent of heterogeneity in the degree distribution, while synchronizability of Type II networks is dependent of both heterogeneity and scale of networks. It is presented the more heterogeneous and larger scale, the poorer synchronizability of Type II networks.

Total variation based model is one of the most effective method for image restoration. In this paper, we consider the total variation (TV) based regularization method and evaluate the regularization parameter for the TV based iterative forward-backward splitting (IFBS) approach. Different parameters with different iterations are obtained. The proposed adaptive iterative forward-backward splitting method does not need to know the initial value of the regularization parameter and does not require any information about the perturbation process. Experimental results demonstrate that the adaptive parameter method is efficient and provide competitive performance.

By using slack variables and minimum function, we first reformulate the system of equalities and inequalities as a system of nonsmooth equations, and, using smoothing technique, we construct the smooth operator. A new noninterior continuation method is proposed to solve the system of smooth equations. It shows that any accumulation point of the iteration sequence generated by our algorithm is a solution of the system of equalities and inequalities. Some numerical experiments show the feasibility and efficiency of the algorithm.

This paper investigates the control law of aero-enginevane angle on dynamic process. Two kinds of corrected algorithm is presented to solve the problem of large perturbation of vane angle at the end of dynamic process. The problem is solved by using the method of slope restriction on perturbation and reducing the amplitude of the perturbation. The effectness of two methods is validated by simulation, and simulation results show that the presented algorithm can be used both individually and associatively. By using these methods, the perturbation of vane angle on dynamic process can be reduced, and accordingly, the stability influence of engine in transition process is ensured better.

This paper considers the static output feedback control synthesis problem of aeroengine system. By introducing a slack variable for separating system matrix and Lyapunov matrix, more relaxed sufficient conditions for designing static output feedback controller are given in terms of solutions to a set of linear matrix inequalities. Simulation illustrates that the proposed methods for aeroengine systems can achieve good performance.

The paper presents a kind of intelligent power management system used in engineering seismograph, which consists of power supply circuit based on power module, and power monitoring circuit based on high speed single chip microcomputers (SCM) C8051F320 and 24-digits high-precision analog-to-digital (A/D) converters LTC2449. The design has features such as wide input range, stable output, self protection, power monitoring and simple user interface etc.