Sliding mode robust fault-tolerant control for uncertain systems with time delay

Considering the modeling uncertainties and external disturbance, a kind of sliding mode robust H∞fault-tolerant control method for time delay system with actuator fault is proposed. The upper-bound of the uncertainties is considered as a known constant, while the upper-bound of the actuator fault is unknown. A sufficient condition for the existence of an integral sliding mode dynamics is given in terms of linear matrix inequality(LMI). A novel adaptive law is given to estimate the unknown upper-bound of faults. On this basis, a type of sliding mode robust H∞fault-tolerant control law is designed to guarantee the asymptotic stability and the H_∞ performance index of the system. Finally, the simulation on quad-rotor semi-physical platform demonstrates the reliability and validity of the method.     

Electronic structures and magneto-transport properties of co-based Heusler alloy based magneto-resistance junctions

A direct link between band structure and the ballistic transport property of full-Heusler alloys based Co₂ YZ/Al/Co₂ YZ trilayers (Y = Sc, Ti, V, Cr, Mn and Fe; Z = Al, Si and Ge) has been studied by firstprinciples calculations. It is found that the transport efficiency is determined primarily by three factors related to band structure: the shape of the band crossing Fermi energy E _F, the distance d of the two intersection points of Co₂ YZ and Al at E _F, and the absolute maximum of the energy lying in the E _F-crossing band, |E_max|. The transmission coefficient distribution patterns imply that the affected factor of magneto-resistance (MR) ratio is attributed to the band features around E _F. In general, an intuitively illustrated diagram is proposed to clarify the relationship between the probability of electron transition and the current magnitude.     

Lattice-based group signature with verifier-local revocation

Among several post quantum primitives proposed in the past few decades, lattice-based cryptography is considered as the most promising one, due to its underlying rich combinatorial structure, and the worst-case to average-case reductions. The first lattice-based group signature scheme with verifier-local revocation(VLR) is treated as the first quantum-resistant scheme supported member revocation, and was put forward by Langlois et al. This VLR group signature(VLR-GS) has group public key size of O(nm log N log q), and a signature size of O(tm log N log q log β). Nguyen et al. constructed a simple efficient group signature from lattice, with significant advantages in bit-size of both the group public key and the signature. Based on their work, we present a VLR-GS scheme with group public key size of O(nm log q) and signature size of O(tm log q). Our group signature has notable advantages: support of membership revocation, and short in both the public key size and the signature size.     

Combustion optimization model for NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> reduction with an improved particle swarm optimization

Abstract: This paper focuses on the combustion optimization to cut down NO _x emission with a new strategy. Firstly, orthogonal experimental design (OED) and chaotic sequences are introduced to improve the performance of particle swarm optimization (PSO). Then, a predicting model for NO _x emission is established on support vector machine (SVM) whose parameters are optimized by the improved PSO. Afterwards, a new optimization model considering coal quantity and air quantity along with the traditional optimization variables is established. At last, the operating parameters are optimized by the improved PSO to cut down the NO _x emission. An application on 600MW unit shows that the new optimization model can cut down NO _x emission effectively and maintain the load balance well. The NO _x emission optimized by the improved PSO is lowest among some state-of-the-art intelligent algorithms. This study can provide important guides for the low NO _x combustion in the power plant.     

Research on Nonlinear Dynamic Simulation and Fatigue Reliability Life Prediction for Synthesis Transmission System of Self-Propelled Gun

Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain, a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear’s complicated torque provided by virtual prototype. The gear’s P-S_a-S_m-N curved cluster can be simulated based on material’s P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear’s fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear’s danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.     

Study on Oxidation Activity of CuCeZrO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> Doped with K for Diesel Engine Particles in NO/O<Subscript>2</Subscript>

CuCeZrO_x and KCuCeZrO_x catalysts were synthesized and coated on the blank diesel particulate filter (DPF) substrate and a particulate matter (PM) loading apparatus was used for soot loading. The catalytic performances of soot oxidation were evaluated by temperature programmed combustion (TPC) test and characterization tests were conducted to investigate the physicochemical properties of the catalysts. The reaction mechanism in the oxidation process was analyzed with diffuse reflectance infrared Fourier transform spectroscopy. The results demonstrated that CuCeZrO_x catalyst exhibited high activities of soot oxidation at low temperature and the best results have been attained with Cu_0.9Ce_0.05Zr_0.05O_x over which the maximum soot oxidation rate decreased to 410 °C. Characterization tests have shown that catalysts containing 90% Cu have uniformly distributed grains and small particle sizes, which provide excellent oxidation activity by providing more active sites and forming a good bond between the catalyst and the soot. The low-temperature oxidation activity of soot could be further optimized due to the excellent elevated NO’s conversion rate by partially substituting Cu with K. The maximum particle oxidation rate can be easily realized at such a low temperature as 347°C.     

Serum levels of RBP4 might not be determined by diabetes mellitus but by kidney function and renal replacement therapy

It has been reported that retinol-binding protein 4(RBP4) is associated to adiposity,insulin resistance,and type 2 diabetes.Meanwhile,circulating RBP4 levels are also affected by renal function.The aim of the present study is to investigate whether serum levels of RBP4 are primarily associated with different stages of chronic kidney disease(CKD) or type 2 diabetes,if there is more potential relevance between RBP4 and renal replacement therapy.The serum levels of RBP4 were assessed by commercial competitive enzyme-linked immunosorbent assay(ELISA)kit in 212 patients with the CKD stages 1—5 and in 24 healthy controls,while its correlation with clinical and metabolic parameters was analyzed.The serum level of RBP4 had a strong correlation with estimated glomerular filtration rate(e GFR)(P 0.001).Stratified by e GFR and treatment,no more differences in RBP4 serum concentration were detected between type 2 diabetic and non-diabetic subjects [CKD stages 1—5,non-dialysis(ND),hemodialysis(HD) and peritoneal dialysis(PD);P 0.05 for all].The elevation of RBP4 become higher in HD than in PD and ND in CKD5 patients(P = 0.008 and P = 0.04,respectively),while there was no significant difference between PD and ND groups.Multivariate linear regression analysis demonstrated three independent predictors of e GFR(β =-0.676,P 0.001),C-reactive protein(CRP)(β =-0.573,P 0.001) and creatine(β = 0.509,P = 0.024) in the study population.The study results demonstrated that the serum level of RBP4 was negatively related to the e GFR,whether diabetes mellitus(DM) affected the blood concentration of RBP4 or not.And the serum level of RBP4 exhibited significant difference in different renal replacement therapies.     

Intelligent Vehicle Human-Simulated Steering Characteristics Access and Control Strategy

As the traditional control algorithm is over-dependent on accurate vehicle model in intelligent vehicle steering control, a human-simulated intelligent control method is proposed based on experienced driver steering characteristics. Intelligent vehicle unmanned steering system dynamics model and the driver model are set up. Through experienced drivers’ trial run experiment, the analysis is mainly conducted on the double lanes condition. After the transformation of coordinates on global positioning system (GPS) derivative, the path information of local coordinates is accessed. The ideal driver steering path is obtained through fuzzy C-means clustering algorithm. The human-simulated intelligent controller is designed. Characteristic model is established according to the ideal and practical steering angle deviation and the deviation rate. Besides, the corresponding control rules and control modality set are designed. The joint simulation under CarSim joint/Simulink environment shows that the humanoid steering controller designed in this paper has better tracking performance than the model predictive control.     

Performance analysis of AF relaying based on water-filling power allocation over Nakagami-<Emphasis Type="Italic">m</Emphasis> fading

This paper investigates exact performance of an amplify-and-forward (AF) relay system based on water-filling power allocation in Nakagami-m fading environment, where m is a nonnegative integer plus one half. We first offer the cumulative distribution function (CDF) and probability density function (PDF) of the received signal-to-noise ratio (SNR) at a destination. Then outage probability, moments of SNR, higher-order statistics of the capacity are explicitly conducted. Especially, average symbol error rate (SER) under an additive white generalized Gaussian noise (AWGGN) is developed for water-filling power allocation scheme. While the average SER subjected by an additive white Gaussian noise (AWGN) can be regarded as a special case. Finally, all theoretical formulas are truly attested by various simulation results.     

基于模糊控制理论的船舶动力定位系统的研究

本文建立了船舶定位系统的数学模型,并设计了系统的模糊控制器。通过仿真得出如下结论:基于Takagi-Sugeno(T-S)模糊模型设计动力定位船舶控制器响应时间,上升时间短,超调率低,具有一定的抗干扰能力,有较强的鲁棒性,具有良好的控制品质。     

Five-axis interpolation of continuous short linear trajectories for 3[PP]S-<Emphasis Type="Italic">XY</Emphasis> hybrid mechanism by dual Bezier blending

A novel five-axis real-time interpolation algorithm for 3[PP]S-XY hybrid mechanism is proposed in this paper. In the algorithm, the five-axis tool path for controlling this hybrid mechanism is separated into two sub-paths. One sub-path describes the movement of 3[PP]S parallel kinematic mechanism module, and the other one describes the movement of XY platform. A pair of cubic Bezier curves is employed to smooth the corners in those two sub-paths. Based on the homogenous Jacobian matrix of 3[PP]S mechanism, a relationship between the position errors of every driving joint in hybrid mechanism and the position deviation of the tool tip center point at the moving platform is established. This relationship is used to estimate the approximation error for the corners smoothing according to the accuracy requirement of tool tip center in interpolation. Due to the high computational efficiency of this corner smoothing method, it is integrated into the look-ahead module of computer numerical control (CNC) system to perform online tool path smoothing. By performing the speed planning based on a floating window scheme, a jerk limited S-shape speed profile can be generated efficiently. On this basis, a realtime look-ahead scheme, which is comprised of path-smoothing and feedrate scheduling, is developed to acquire a speed profile with smooth acceleration. A monotonic cubic spline is employed for synchronization between those two smoothed sub-paths in tool path interpolation. This interpolation algorithm has been integrated into our own developed CNC system to control a 3PRS-XY experimental instrument (P, R and S standing for prismatic, revolute and spherical, respectively). A club shaped trajectory is adopted to verify the smoothness and efficiency of the five-axis interpolator for hybrid mechanism control.     

Calculation of 3D sensitivity matrix for electromagnetic tomography system using boundary elements and the perturbative approach

Electromagnetic tomography （EMT） is a non-invasive imaging technique capable of mapping the conductivity and permeability of an object. In EMT, eddy currents are induced in the object by the activation coils, and the receiving coils can measure the EMT voltages. When the activation frequency is significantly large, we can treat the metallic targets as electrically perfect conductors （EPCs）. In this situation, a thin skin approximation is reasonable and this type of scattering problem can be effectively treated by the boundary element method （BEM） formulated through integration equations. In this study, we compute three-dimensional （3D） sensitivity matrix between the sensors due to an EPC perturbation. Efficiency improvement is achieved through the utility of scalar magnetic potential. Two EPC objects, one sphere and one cube shaped, are simulated. The results agree well with the H dot H formula. Overall, we conclude that BEM can be used to calculate the 3D sensitivity matrix of an EMT system efficiently. This method is a general one for any shaped objects while the H dot H solution is only capable of producing the response for a small ball.     

The numerical simulation of a towing cylinder based on immersed body boundary method

An immersed body boundary method is adopted to track the motions of a towing cylinder, and a homogenous multiphase Eulerian-Eulerian fluid approach is used to capture the free surface. The Reynolds average Navier-Stockes (RANS) solver is applied to all gird nodes to deal with different velocities of the nodes that are in the body boundary, near the boundary and out of the boundary and their effect on the fluid. The towing cylinder resistance at different submerged depths in the tank is presented. The simulation results are compared with the experimental data, and the method is verified and validated. Finally, the hydrodynamic characters of the cylinder are discussed further. The numerical and experimental results show that at high speeds, the deeper the cylinder submerges, the lower resistance it suffers. The resistance coefficient trough is obtained at Froude number in the range of 0.3 < F r < 0.4. These phenomena can provide some suggestions on the small waterplane area twin hull (SWATH) design.     

基于模糊线性模型的舵减横摇广义预测控制

舵减摇技术是一项新的减摇技术,通常其控制器设计所用的舰船模型为通用线性模型,对实际上为非线性被控对象的控制性能要下降.文中依据非线性舰船模型,应用模糊神经网络简化出适应于舵减横摇控制器设计的模糊线性模型,并设计了广义预测控制器.在典型航行工况下进行系统仿真.仿真结果表明,针对模糊线性模型和通用线性模型,用同一种方法与参数设计的2个控制器,前者的减摇率可达到40.70%,要高于后者的25.38%.仿真证明了模糊线性模型的可用性.     

A relaxed-PPA contraction method for sparse signal recovery

Sparse signal recovery is a topic of considerable interest, and the literature in this field is already quite immense. Many problems that arise in sparse signal recovery can be generalized as a convex programming with linear conic constraints. In this paper, we present a new proximal point algorithm (PPA) termed as relaxed-PPA (RPPA) contraction method, for solving this common convex programming. More precisely, we first reformulate the convex programming into an equivalent variational inequality (VI), and then efficiently explore its inner structure. In each step, our method relaxes the VI-subproblem to a tractable one, which can be solved much more efficiently than the original VI. Under mild conditions, the convergence of the proposed method is proved. Experiments with l ₁ analysis show that RPPA is a computationally efficient algorithm and compares favorably with the recently proposed state-of-the-art algorithms.     

Catalytic Combustion of Lean Methane Assisted by Electric Field over Pd/Co<Subscript>3</Subscript>O<Subscript>4</Subscript> Catalysts at Low Temperature

A series of Pd/Co₃O₄ catalysts were prepared by Self-Propagating High-Temperature Synthesis (SHS) method in this study, and electric field was applied for catalytic combustion of lean methane over Pd/Co₃O₄ catalysts at low temperature. When electric field was applied, the catalytic combustion performance of Pd/Co₃O₄ catalysts was greatly improved, and the application of electric field could reduce the load of active element Pd to some extent while maintaining the same efficiency. Based on experimental tests and the analysis results of X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), H₂-temperature-programmed reduction (H₂-TPR) and in-situ diffuse reflectance infrared Fourier transform spectroscopy (in-situ DRIFTS), the mechanism of catalytic oxidation of CH₄ over Pd/Co₃O₄ catalysts in electric field was proposed. The catalytic combustion of CH₄ occurs only when the temperature is higher than 250 °C normally, but when electric field was applied, the whole process of CH₄ oxidation was promoted significantly and the reaction temperature was reduced. Electric field could promote the reduction of the support Co₃O₄ to release the lattice oxygen, resulting in the increase of PdO_x and the surface chemisorbed oxygen, which could provide more active sites for the low-temperature oxidation of CH₄. Furthermore, electric field could accelerate the dehydroxylation of CoOOH to further enhance the activity of the catalysts.     

H ∞ parameter identification and H 2 feedback control synthesizing for inflight aircraft icing

Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the principle of aircraft icing and its effects on flight performance. The onboard icing detection equipment can only give the qualitative icing information, but cannot effectively describe how serious the consequences would be. If the icing detection equipment fails, it will cause a serious threat to flight safety. This paper reviews the smart icing system and its fundamental principle. Then based on H∞ theory, an aircraft icing parameter identification method is introduced, and its feasibility is verified by simulation results. Moreover, this method can work normally under noise interference and measurement error. Icing parameter identification method can also test part of aircraft’s stability or control derivatives which would be changed obviously after aircraft icing. Classified by neural networks, the stability or control derivatives’ variation can be mapped to ice parameters’ variation that reflects the severity of aircraft icing. Then H2 state feedback control is designed originally to suppress the impact of noise interference, so aircraft can keep steady after it is iced. Seeing from simulation result of the whole system, it is clear that the system can effectively detect icing parameters and by using feedback control system, it can ensure the safety of aircraft in the flight envelope.     

Observer-based adaptive neural iterative learning control for a class of time-varying nonlinear systems

In this paper an adaptive iterative learning control scheme is presented for the output tracking of a class of nonlinear systems. An observer is designed to estimate the tracking errors. A mixed time domain and s-domain representation is constructed to derive an error model with relative degree one for our purpose. And time-varying radial basis function neural network is employed to deal with system uncertainty. A new signal is constructed by using a first-order filter, which removes the requirement of strict positive real (SPR) condition and identical initial condition of iterative learning control. Based on property of hyperbolic tangent function, the system tracing error is proved to converge to the origin as the iteration tends to infinity by constructing Lyapunov-like composite energy function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.     

一类非线性不确定时滞系统鲁棒控制器的设计

利用LMI方法,针对不确定时滞系统的鲁棒模糊控制器设计及稳定性,提出了基于T—S的模糊模型,得到了使系统渐近稳定且具有H∞-扰动抑制度的模糊状态反馈控制器存在的充分条件,此充分条件以线性矩阵不等式的形式给出,因而具有数值易解性．     

基于GA-FC的船舶减摇鳍控制仿真研究

根据船舶减摇鳍控制系统在不同海情下的期望减摇效果,设计了不同的性能指标,运用遗传算法离线优化设计模糊控制器,组建控制系统知识库.控制程序根据船舶实时的运行情况,调用系统知识库中相应的控制器,并在线修正GA-FC控制器的比例因子,进一步增强系统的自适应能力.仿真结果表明,基于遗传模糊算法的船舶减摇鳍在线控制系统,具有很好的减摇控制效果,并减缓了鳍角饱和概率和转鳍角速度,从而降低了鳍伺服系统的功耗.