Journal of Control Science and Engineering The latest articles from Hindawi © 2017 , Hindawi Limited . All rights reserved. Providing Definitive Learning Direction for Relation Classification System Thu, 12 Oct 2017 00:00:00 +0000 Deep neural network has adequately revealed its superiority of solving various tasks in Natural Language Processing, especially for relation classification. However, unlike traditional feature-engineering methods that targetedly extract well-designed features for specific task, the diversity of input format for deep learning is limited; word sequence as input is the frequently used setting. Therefore, the input of neural network, to some extent, lacks pertinence. For relation classification task, it is not uncommon that, without specific entity pair, a sentence contains various relation types; therefore, entity pair indicates the distribution of the crucial information in input sentence for recognizing specific relation. Aiming at this characteristic, in this paper, several strategies are proposed to integrate entity pair information into the application of deep learning in relation classification task, in a way to provide definitive learning direction for neural network. Experimental results on the SemEval-2010 Task 8 dataset show that our method outperforms most of the state-of-the-art models, without external linguistic features. Pengda Qin, Weiran Xu, and Jun Guo Copyright © 2017 Pengda Qin et al. All rights reserved. A Fault Diagnosis Method for Oil Well Pump Using Radial Basis Function Neural Network Combined with Modified Genetic Algorithm Sun, 08 Oct 2017 00:00:00 +0000 This paper presents a new method to diagnose oil well pump faults using a modified radial basis function neural network. With the development of submersible linear motor technology, rodless pumping units have been widely used in oil exploration. However, the ground indicator diagram method cannot be used to diagnose the working conditions of rodless pumping units because it is based on the load change of the polished rod suspension point and its displacement. To solve this problem, this paper presents a new method that is applicable to rodless oil pumps. The advantage of this new method is its use of a simple feature extraction method and advanced genetic algorithm to optimize the threshold and weight of the RBF neural network. In this paper, we extract the characteristic value from the operation parameters of the submersible linear motor and oil wellhead as the input vector of the fault diagnosis model. Through experimental analysis, the proposed method is proven to have good convergence performance, high accuracy, and high reliability. Deliang Yu, Yanmei Li, Hao Sun, Yulong Ren, Yongming Zhang, and Weigui Qi Copyright © 2017 Deliang Yu et al. All rights reserved. Direct Power Control Strategy of PWM Rectifier Based on Improved Virtual Flux-Linkage Observer Mon, 02 Oct 2017 00:00:00 +0000 In order to achieve the low cost and high performance control of three-phase PWM rectifier, a direct power control (DPC) strategy based on a new-style virtual flux-linkage observer is proposed. The model of three-phase PWM rectifier and the principle of virtual flux-linkage vector control are introduced firstly. Then, in order to avoid the effect of integral initial value and cumulative deviation, three first-order low-pass filters are cascaded to replace the pure integral link; an improved virtual flux-linkage observer of three-phase power grid is presented. From the observed virtual flux-linkage, the voltage and instantaneous power of three-phase power grid are online estimated. On this basis, the power grid voltage sensorless direct power control system of three-phase PWM rectifier is designed. Simulation results have shown that, both in the rectifying state and in the inverting state, the power grid side current and the DC side voltage of three-phase PWM rectifier all can be effectively controlled; the high power factor operation of three-phase PWM rectifier is realized. Wenshao BU and Leilei Xu Copyright © 2017 Wenshao BU and Leilei Xu. All rights reserved. A Bayesian Approach to Control Loop Performance Diagnosis Incorporating Background Knowledge of Response Information Thu, 28 Sep 2017 09:40:00 +0000 To isolate the problem source degrading the control loop performance, this work focuses on how to incorporate background knowledge into Bayesian inference. In an effort to reduce dependence on the amount of historical data available, we consider a general kind of background knowledge which appears in many applications. The knowledge, known as response information, is about what faults can possibly affect each of the monitors. We show how this knowledge can be translated to constraints on the underlying probability distributions and introduced in the Bayesian diagnosis. In this way, the dimensionality of the observation space is reduced and thus the diagnosis can be more reliable. Furthermore, for the judgments to be consistent, the set of posterior probabilities of each possible abnormality that are computed from different observation subspaces is synthesized to obtain the partially ordered posteriors. The eigenvalue formulation is used on the pairwise comparison matrix. The proposed approach is applied to a diagnosis problem on an oil sand solids handling system, where it is shown how the combination of background knowledge and data enhances the control performance diagnosis even when the abnormality data are sparse in the historical database. Sun Zhou and Yiming Wang Copyright © 2017 Sun Zhou and Yiming Wang. All rights reserved. Adaptive Sliding Mode Control of MEMS AC Voltage Reference Source Wed, 20 Sep 2017 00:00:00 +0000 The accuracy of physical parameters of a tunable MEMS capacitor, as the major part of MEMS AC voltage reference, is of great importance to achieve an accurate output voltage free of the malfunctioning noise and disturbance. Even though strenuous endeavors are made to fabricate MEMS tunable capacitors with desiderated accurate physical characteristics and ameliorate exactness of physical parameters’ values, parametric uncertainties ineluctably emerge in fabrication process attributable to imperfections in micromachining process. First off, this paper considers applying an adaptive sliding mode controller design in the MEMS AC voltage reference source so that it is capable of giving off a well-regulated output voltage in defiance of jumbling parametric uncertainties in the plant dynamics and also aggravating external disturbance imposed on the system. Secondly, it puts an investigatory comparison with the designed model reference adaptive controller and the pole-placement state feedback one into one’s prospective. Not only does the tuned adaptive sliding mode controller show remarkable robustness against slow parameter variation and external disturbance being compared to the pole-placement state feedback one, but also it immensely gets robust against the external disturbance in comparison with the conventional adaptive controller. The simulation results are promising. Ehsan Ranjbar, Ali Mehrnezhad, and Amir Abolfazl Suratgar Copyright © 2017 Ehsan Ranjbar et al. All rights reserved. Corrigendum to “Empirical Reduced-Order Modeling for Boundary Feedback Flow Control” Tue, 19 Sep 2017 00:00:00 +0000 Seddik M. Djouadi, R. Chris Camphouse, and James H. Myatt Copyright © 2017 Seddik M. Djouadi et al. All rights reserved. Event-Driven Control for NCSs with Logarithmic Quantization and Packet Losses Sun, 17 Sep 2017 00:00:00 +0000 The stabilization problem of the networked control systems (NCSs) affected by data quantization, packet losses, and event-driven communication is studied in this paper. By proposing two event-driven schemes and the extended forms of them relying on quantized states, zoom strategy is adopted here to study the system stability with time-varying logarithmic quantization and independent identically distributed (IID) packet losses process. On the basis of that, some sufficient conditions ensuring the mean square stability of the system are obtained here. Although zoom strategy has been utilized by many literatures to study the quantized stabilization problem of NCSs, it has not been adopted to analyze the stability of NCSs with data quantization, IID packet losses, and event-driven communication. Furthermore, the existing literatures relating to zoom strategy employ the quantizer with quantization regions holding arbitrary shapes, but here we use the logarithmic quantizer which holds better performance near the origin. In addition, the detailed comparisons of the system performance under different event-driven schemes are given here, which can guide the strategy selection according to the different design goals. The above three points are the main innovations of this paper. At last, the effectiveness of the proposed methods is illustrated by a benchmark example. Jingjing Yan Copyright © 2017 Jingjing Yan. All rights reserved. An Optimized Replica Distribution Method in Cloud Storage System Tue, 12 Sep 2017 00:00:00 +0000 Aiming at establishing a shared storage environment, cloud storage systems are typical applications of cloud computing. Therefore, data replication technology has become a key research issue in storage systems. Considering the performance of data access and balancing the relationship between replica consistency maintenance costs and the performance of multiple replicas access, the methods of replica catalog design and the information acquisition method are proposed. Moreover, the deputy catalog acquisition method to design and copy the information is given. Then, the nodes with the global replica of the information replicate data resources, which have the high access frequency and the long response time. Afterwards, the Markov chain model is constructed. And a matrix geometric solution is used to export the steady-state solution of the model. The performance parameters in terms of the average response time, finish time, and the replica frequency are given to optimize the number of replicas in the storage system. Finally, numerical results with analysis are proposed to demonstrate the influence of the above parameters on the system performance. Yan Wang and Jinkuan Wang Copyright © 2017 Yan Wang and Jinkuan Wang. All rights reserved. Nonlinear Dynamics of a PI Hydroturbine Governing System with Double Delays Tue, 12 Sep 2017 00:00:00 +0000 A PI hydroturbine governing system with saturation and double delays is generated in small perturbation. The nonlinear dynamic behavior of the system is investigated. More precisely, at first, we analyze the stability and Hopf bifurcation of the PI hydroturbine governing system with double delays under the four different cases. Corresponding stability theorem and Hopf bifurcation theorem of the system are obtained at equilibrium points. And then the stability of periodic solution and the direction of the Hopf bifurcation are illustrated by using the normal form method and center manifold theorem. We find out that the stability and direction of the Hopf bifurcation are determined by three parameters. The results have great realistic significance to guarantee the power system frequency stability and improve the stability of the hydropower system. At last, some numerical examples are given to verify the correctness of the theoretical results. Hongwei Luo, Jiangang Zhang, Wenju Du, Jiarong Lu, and Xinlei An Copyright © 2017 Hongwei Luo et al. All rights reserved. Study of Error Propagation in the Transformations of Dynamic Thermal Models of Buildings Wed, 06 Sep 2017 00:00:00 +0000 Dynamic behaviour of a system may be described by models with different forms: thermal (RC) networks, state-space representations, transfer functions, and ARX models. These models, which describe the same process, are used in the design, simulation, optimal predictive control, parameter identification, fault detection and diagnosis, and so on. Since more forms are available, it is interesting to know which one is the most suitable by estimating the sensitivity of the model to transform into a physical model, which is represented by a thermal network. A procedure for the study of error by Monte Carlo simulation and of factor prioritization is exemplified on a simple, but representative, thermal model of a building. The analysis of the propagation of errors and of the influence of the errors on the parameter estimation shows that the transformation from state-space representation to transfer function is more robust than the other way around. Therefore, if only one model is chosen, the state-space representation is preferable. Loïc Raillon and Christian Ghiaus Copyright © 2017 Loïc Raillon and Christian Ghiaus. All rights reserved. Study on a High-Accuracy Real-Time Algorithm to Estimate SOC of Multiple Battery Cells Simultaneously Wed, 30 Aug 2017 07:47:12 +0000 In traditional battery equalization strategy, open-circuit voltage (OCV) of battery cells was used to judge the difference of SOC between them. However, OCV is not only determined by SOC but also influenced by internal resistance, polarization voltage, capacity, and other nonlinear factors. As a result, OCV is not an ideal indicator of SOC differences, especially in transient conditions. In order to control battery consistency accurately, it is best to use SOC directly as standard for battery consistency judgment and control. To achieve this, an algorithm that can estimate SOC of multiple battery cells simultaneously with low computational complexity and high accuracy is needed. Limited by computing speed of Battery Control Unit (BCU), existing SOC estimation method is hard to estimate SOC of each battery cell simultaneously with high accuracy. In this research, a new SOC estimation strategy was proposed to estimate SOC of multiple battery cells simultaneously for battery equalization control. Battery model is established based on experimental data, and a processor-in-the-loop test system was established to verify the actual performance of the proposed algorithm. Results of simulation and test indicate that the proposed algorithm can estimate SOC of multiple battery cells simultaneously and achieved good real-time performance and high accuracy. Yong Luo, Yingzhe Kan, Yanli Yin, Li Liu, Huanyu Cui, and Fei Wu Copyright © 2017 Yong Luo et al. All rights reserved. Predictive Control of Mobile Robot Using Kinematic and Dynamic Models Mon, 28 Aug 2017 00:00:00 +0000 This paper presents a predictive control of omnidirectional mobile robot with three independent driving wheels based on kinematic and dynamic models. Two predictive controllers are developed. The first is based on the kinematic model and the second is founded on the dynamic model. The optimal control sequence is obtained by minimizing a quadratic performance criterion. A comparison has been done between the two controllers and simulations have been done to show the effectiveness of the predictive control with the kinematic and the dynamic models. Manel Mendili and Faouzi Bouani Copyright © 2017 Manel Mendili and Faouzi Bouani. All rights reserved. Online Model Learning of Buildings Using Stochastic Hybrid Systems Based on Gaussian Processes Wed, 23 Aug 2017 00:00:00 +0000 Dynamical models are essential for model-based control methodologies which allow smart buildings to operate autonomously in an energy and cost efficient manner. However, buildings have complex thermal dynamics which are affected externally by the environment and internally by thermal loads such as equipment and occupancy. Moreover, the physical parameters of buildings may change over time as the buildings age or due to changes in the buildings’ configuration or structure. In this paper, we introduce an online model learning methodology to identify a nonparametric dynamical model for buildings when the thermal load is latent (i.e., the thermal load cannot be measured). The proposed model is based on stochastic hybrid systems, where the discrete state describes the level of the thermal load and the continuous dynamics represented by Gaussian processes describe the thermal dynamics of the air temperature. We demonstrate the evaluation of the proposed model using two-zone and five-zone buildings. The data for both experiments are generated using the EnergyPlus software. Experimental results show that the proposed model estimates the thermal load level correctly and predicts the thermal behavior with good performance. Hamzah Abdel-Aziz and Xenofon Koutsoukos Copyright © 2017 Hamzah Abdel-Aziz and Xenofon Koutsoukos. All rights reserved. T-S Fuzzy Model Based -Infinity Control for 7-DoF Automobile Electrohydraulic Active Suspension System Sun, 20 Aug 2017 00:00:00 +0000 This paper presents a double loop controller for a 7-DoF automobile electrohydraulic active suspension via T-S fuzzy modelling technique. The outer loop controller employs a modified -infinity feedback control based on a T-S fuzzy model to provide the actuation force needed to ensure better riding comfort and handling stability. The resulting optimizing problem is transformed into a linear matrix inequalities solution issue associated with stability analysis, suspension stroke limit, and force constraints. Integrating these via parallel distributed compensation method, the feedback gains are derived to render the suspension performance dependent on the perturbation size and improve the efficiency of active suspensions. Adaptive Robust Control (ARC) is then adopted in the inner loop design to deal with uncertain nonlinearities and improve tracking accuracy. The validity of improvements attained from this controller is demonstrated by comparing with conventional Backstepping control and a passive suspension on a 7-DoF simulation example. It is shown that the T-S fuzzy model based controller can achieve favourable suspension performance and energy conservation under both mild and malevolent road inputs. Chenyu Zhou, Qiang Yu, Xuan Zhao, and Guohua Zhu Copyright © 2017 Chenyu Zhou et al. All rights reserved. Contrastive Study on Torque Distribution of Distributed Drive Electric Vehicle under Different Control Methods Thu, 17 Aug 2017 08:28:40 +0000 This paper uses certain hub motor distributed electric vehicle driving system as the research object, using several control strategies, such as dynamic programming global optimization algorithm, fuzzy control, and torque equal distribution and realizing the distribution control of the distributed power of the electric drive system. The simulation results show that, under the NEDC road condition, using the dynamic programming algorithm to optimize the torque distribution, the energy consumption of the electric drive system is 8041 kJ, decreased by 4.77% compared to the average torque distribution control and decreased by 3.5% compared to the fuzzy control strategy. The power consumption of the electric vehicle is 20.25 kWh per 100 km, decreased by 1.01 kWh compared to the average torque distribution control strategy and decreased by 0.72 kWh compared to the fuzzy control strategy. Under the fixed working condition, the energy efficiency of power system can be improved effectively when the distributed dynamic system torque is optimized by the dynamic programming algorithm. Without considering the global optimization, the fuzzy control can effectively improve the energy efficiency of the power system compared to the torque average distribution strategy. Xiao-gang Wu and Dian-yu Zheng Copyright © 2017 Xiao-gang Wu and Dian-yu Zheng. All rights reserved. Synchronization of Two Fractional-Order Chaotic Systems via Nonsingular Terminal Fuzzy Sliding Mode Control Thu, 17 Aug 2017 00:00:00 +0000 The synchronization of two fractional-order complex chaotic systems is discussed in this paper. The parameter uncertainty and external disturbance are included in the system model, and the synchronization of the considered chaotic systems is implemented based on the finite-time concept. First, a novel fractional-order nonsingular terminal sliding surface which is suitable for the considered fractional-order systems is proposed. It is proven that once the state trajectories of the system reach the proposed sliding surface they will converge to the origin within a given finite time. Second, in terms of the established nonsingular terminal sliding surface, combining the fuzzy control and the sliding mode control schemes, a novel robust single fuzzy sliding mode control law is introduced, which can force the closed-loop dynamic error system trajectories to reach the sliding surface over a finite time. Finally, using the fractional Lyapunov stability theorem, the stability of the proposed method is proven. The proposed method is implemented for synchronization of two fractional-order Genesio-Tesi chaotic systems with uncertain parameters and external disturbances to verify the effectiveness of the proposed fractional-order nonsingular terminal fuzzy sliding mode controller. Xiaona Song, Shuai Song, Ines Tejado Balsera, Leipo Liu, and Lei Zhang Copyright © 2017 Xiaona Song et al. All rights reserved. MPPT Control Strategy of PV Based on Improved Shuffled Frog Leaping Algorithm under Complex Environments Tue, 15 Aug 2017 00:00:00 +0000 This work presents a maximum power point tracking (MPPT) based on the particle swarm optimization (PSO) improved shuffled frog leaping algorithm (PSFLA). The swarm intelligence algorithm (SIA) has vast computing ability. The MPPT control strategies of PV array based on SIA are attracting considerable interests. Firstly, the PSFLA was proposed by adding the inertia weight factor of PSO in standard SFLA to overcome the defect of falling into the partial optimal solutions and slow convergence speed. The proposed PSFLA algorithm increased calculation speed and excellent global search capability of MPPT. Then, the PSFLA was applied to MPPT to solve the multiple extreme point problems of nonlinear optimization. Secondly, for the problems of MPPT under complex environments, a new MPPT strategy of the PSFLA combined with recursive least square filtering was proposed to overcome the measurement noise effects on MPPT accuracy. Finally, the simulation comparisons between PSFLA and SFLA algorithm were developed. The experiment and comparison between PSLFA and PSO algorithm under complex environment were executed. The simulation and experiment results indicate that the proposed MPPT control strategy based on PSFLA can suppress the measurement noise effects effectively and improve the PV array efficiency. Xiaohua Nie and Haoyao Nie Copyright © 2017 Xiaohua Nie and Haoyao Nie. All rights reserved. Self-Adaptive Artificial Bee Colony for Function Optimization Mon, 14 Aug 2017 00:00:00 +0000 Artificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concerning its position-updated equation, which is skilled in global search and bad at local search. In order to coordinate the ability of global and local search, we first propose a self-adaptive ABC algorithm (denoted as SABC) in which an improved position-updated equation is used to guide the search of new candidate individuals. In addition, good-point-set approach is introduced to produce the initial population and scout bees. The proposed SABC is tested on 12 well-known problems. The simulation results demonstrate that the proposed SABC algorithm has better search ability with other several ABC variants. Mingzhu Tang, Wen Long, Huawei Wu, Kang Zhang, and Yuri A. W. Shardt Copyright © 2017 Mingzhu Tang et al. All rights reserved. Remaining Useful Life Estimation Based on Asynchronous Multisource Monitoring Information Fusion Sun, 13 Aug 2017 10:19:24 +0000 An asynchronous RUL fusion estimation algorithm is presented for the hidden degradation process with multiple asynchronous monitoring sensors based on multisource information fusion. Firstly, a state-space type model is established by modeling the stochastic degradation as a Wiener process and transforming asynchronous indirectly observations in the fusion period to the fusion time. The statistical characteristics of involved noises and their correlations are analyzed. Secondly, the estimate of the hidden degradation state is obtained by applying Kalman filtering with correlated noises to the established state-space model, where the synchronized observations are fused. Also, the unknown model parameters are recursively identified based on the Expectation-Maximization (EM) algorithm with the Generic Algorithm (GA) adopted to solve the maximization problem. Finally, the probability distribution of RUL is obtained using the fused degradation state estimation and the updated identification result of the model parameters. Simulation results show that the proposed fusion method has better performance than the RUL estimation with single sensor. Yanyan Hu, Shuai Qi, Xiaoling Xue, and Kaixiang Peng Copyright © 2017 Yanyan Hu et al. All rights reserved. Fault Diagnosis of Nonlinear Uncertain Systems with Triangular Form Tue, 01 Aug 2017 09:38:03 +0000 A novel approach to fault diagnosis for a class of nonlinear uncertain systems with triangular form is proposed in this paper. It is based on the extended state observer (ESO) of the active disturbance rejection controller and linearization of dynamic compensation. Firstly, an ESO is designed to jointly estimate the states and the combination of uncertainty, faults, and nonlinear function of nonlinear uncertain systems. It can derive the estimation of nonlinear function via the state estimations and system model. Then, linearization of dynamic compensation is employed to linearize the system by offsetting nonlinear function mandatorily using its estimation. An observer-based residual generator is designed on the basis of the prior linearized model for fault diagnosis. Moreover, threshold treatment technique is adopted to improve the robustness of fault diagnosis. This method is utilizable and simple in construction and parameter tuning. And also we show the construction of ESO and give the corresponding convergence proof succinctly. Finally, a numerical example is presented to illustrate the validity of the proposed fault diagnosis scheme. Qi Ding, Xiafu Peng, Xunyu Zhong, and Xiaoqiang Hu Copyright © 2017 Qi Ding et al. All rights reserved. Control of Energy Storage Systems for Aeronautic Applications Wed, 19 Jul 2017 08:41:28 +0000 Future aircraft will make more and more use of automated electric power system management onboard. Different solutions are currently being explored, and in particular the use of a supercapacitor as an intelligent energy storage device is addressed in this paper. The main task of the supercapacitor is to protect the electric generator from abrupt power changes resulting from sudden insertion or disconnection of loads or from loads with regenerative power capabilities, like electromagnetic actuators. A controller based on high-gain concepts is designed to drive a DC/DC converter connecting the supercapacitor to the main electric bus. Formal stability proofs are given for the resulting nonlinear system, and strong robustness results from the use of high-gain and variable structure control implementation. Moreover, detailed simulations including switching devices and electrical parasitic elements are provided for different working scenarios, showing the effectiveness of the proposed solution. G. Canciello, A. Cavallo, and B. Guida Copyright © 2017 G. Canciello et al. All rights reserved. Thermal Model Parameter Identification of a Lithium Battery Thu, 13 Jul 2017 00:00:00 +0000 The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS) take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities) can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements. Dirk Nissing, Arindam Mahanta, and Stefan van Sterkenburg Copyright © 2017 Dirk Nissing et al. All rights reserved. Distributed Control of Networked Agent Systems: Theory and Applications Wed, 12 Jul 2017 08:52:03 +0000 Guanghui Wen, Haibo Du, Chaojie Li, Qiang Song, and Wenwu Yu Copyright © 2017 Guanghui Wen et al. All rights reserved. Synchronization of Coupled Harmonic Oscillators Using Quantized Sampled Position Data Mon, 03 Jul 2017 00:00:00 +0000 For coupled harmonic oscillators (CHO), the paper studies the synchronization problem by using the quantized current sampled position data. The logarithmic quantizer is adopted here to quantize the information transmitted; thus the quantization error of the sampled position data can be illustrated as the uncertainty according to the sector bound property. On the basis of that, the synchronization problem is converted into the asymptotical stability of the subsystems and even the solving problem of characteristic equation. Some sufficient conditions ensuring the synchronization of CHO are obtained relating to coupling strength, sampling period, and quantizer parameter. The usefulness of the theoretical result is shown by an example at the end. Xinjing Wang and Peipei He Copyright © 2017 Xinjing Wang and Peipei He. All rights reserved. A Novel Measurement Matrix Optimization Approach for Hyperspectral Unmixing Mon, 03 Jul 2017 00:00:00 +0000 Each pixel in the hyperspectral unmixing process is modeled as a linear combination of endmembers, which can be expressed in the form of linear combinations of a number of pure spectral signatures that are known in advance. However, the limitation of Gaussian random variables on its computational complexity or sparsity affects the efficiency and accuracy. This paper proposes a novel approach for the optimization of measurement matrix in compressive sensing (CS) theory for hyperspectral unmixing. Firstly, a new Toeplitz-structured chaotic measurement matrix (TSCMM) is formed by pseudo-random chaotic elements, which can be implemented by a simple hardware; secondly, rank revealing QR factorization with eigenvalue decomposition is presented to speed up the measurement time; finally, orthogonal gradient descent method for measurement matrix optimization is used to achieve optimal incoherence. Experimental results demonstrate that the proposed approach can lead to better CS reconstruction performance with low extra computational cost in hyperspectral unmixing. Su Xu and Xiping He Copyright © 2017 Su Xu and Xiping He. All rights reserved. Parameter Identification and Control Scheme for Monitoring Automatic Thickness Control System with Measurement Delay Wed, 21 Jun 2017 00:00:00 +0000 The thickness of the steel strip is an important indicator of the overall strip quality. Deviations in thickness are primarily controlled using the automatic gauge control (AGC) system of each rolling stand. At the last stand, the monitoring AGC system is usually used, where the deviations in thickness can be directly measured by the X-ray thickness gauge device and used as the input to the AGC system. However, due to the physical distance between the thickness detection device and the rolling stand, time delay is unavoidably present in the thickness control loop, which can affect control performance and lead to system oscillations. Furthermore, the parameters of the system can change due to perturbations from external disturbances. Therefore, this paper proposes an identification and control scheme for monitoring AGC system that can handle time delay and parameter uncertainty. The cross-correlation function is used to estimate the time delay of the system, while the system parameters are identified using a recursive least squares method. The time delay and parameter estimates are then further refined using the Levenberg-Marquardt algorithm, so as to provide the most accurate parameter estimates for the complete system. Simulation results show that, compared with the standard Proportion Integration Differentiation (PID) controller approach, the proposed approach is not affected by changes in the time delay and parameter uncertainties. Xu Yang, Jingjing Gao, Yuri A. W. Shardt, Linlin Li, and Chaonan Tong Copyright © 2017 Xu Yang et al. All rights reserved. Stability and Hopf Bifurcation for a Delayed Computer Virus Model with Antidote in Vulnerable System Tue, 20 Jun 2017 00:00:00 +0000 A delayed computer virus model with antidote in vulnerable system is investigated. Local stability of the endemic equilibrium and existence of Hopf bifurcation are discussed by analyzing the associated characteristic equation. Further, direction of the Hopf bifurcation and stability of the bifurcating periodic solutions are investigated by using the normal form theory and the center manifold theorem. Finally, numerical simulations are presented to show consistency with the obtained results. Zizhen Zhang, Yougang Wang, and Massimiliano Ferrara Copyright © 2017 Zizhen Zhang et al. All rights reserved. A Real-Time Structure of Attitude Algorithm for High Dynamic Bodies Sun, 18 Jun 2017 09:48:38 +0000 To solve the real-time problem of attitude algorithm for high dynamic bodies, a real-time structure of attitude algorithm is developed by analyzing the conventional structure that has two stages, and a flow diagram of a real-time structure for a Matlab program is provided in detail. During the update of the attitude matrix, the real-time structure saves every element of attitude matrix in minor loop in real time and updates the next attitude matrix based on the previous matrix every subsample time. Thus, the real-time structure avoids lowering updating frequency, though the multisubsample algorithms are used. Simulation and analysis show that the real-time structure of attitude algorithm is better than the conventional structure due to short update time of attitude matrix and small drifting error, and it is more appropriate for high dynamic bodies. Xingcheng Li and Shuangbiao Zhang Copyright © 2017 Xingcheng Li and Shuangbiao Zhang. All rights reserved. An Out Space Accelerating Algorithm for Generalized Affine Multiplicative Programs Problem Wed, 14 Jun 2017 08:31:58 +0000 This paper presents an out space branch-and-bound algorithm for solving generalized affine multiplicative programs problem. Firstly, by introducing new variables and constraints, we transform the original problem into an equivalent nonconvex programs problem. Secondly, by utilizing new linear relaxation technique, we establish the linear relaxation programs problem of the equivalent problem. Thirdly, based on the out space partition and the linear relaxation programs problem, we construct an out space branch-and-bound algorithm. Fourthly, to improve the computational efficiency of the algorithm, an out space reduction operation is employed as an accelerating device for deleting a large part of the investigated out space region. Finally, the global convergence of the algorithm is proved, and numerical results demonstrate the feasibility and effectiveness of the proposed algorithm. Lei Cai, Shuai Tang, Jingben Yin, Zhisong Hou, and Hongwei Jiao Copyright © 2017 Lei Cai et al. All rights reserved. An Effective Algorithm for Globally Solving Sum of Linear Ratios Problems Mon, 05 Jun 2017 08:31:35 +0000 In this study, we propose an effective algorithm for globally solving the sum of linear ratios problems. Firstly, by introducing new variables, we transform the initial problem into an equivalent nonconvex programming problem. Secondly, by utilizing direct relaxation, the linear relaxation programming problem of the equivalent problem can be constructed. Thirdly, in order to improve the computational efficiency of the algorithm, an out space pruning technique is derived, which offers a possibility of pruning a large part of the out space region which does not contain the optimal solution of the equivalent problem. Fourthly, based on out space partition, by combining bounding technique and pruning technique, a new out space branch-and-bound algorithm for globally solving the sum of linear ratios problems (SLRP) is designed. Finally, numerical experimental results are presented to demonstrate both computational efficiency and solution quality of the proposed algorithm. Hongwei Jiao, Lei Cai, Zhisong Hou, and Chunyang Bai Copyright © 2017 Hongwei Jiao et al. All rights reserved.