Adaptive chatter mitigation control for machining processes with input saturations

Chatter is an unstable nonlinear dynamical phenomenon often encountered in machining operations because of the self‐excitation mechanism, which may lead to overcut or rapid tool wear, and hence, greatly influence the surface quality and productivity in milling operations. Recent years have witnessed an increasing industrial demand of high quality and high efficiency machining. This paper hereby develops a constrained active adaptive control method to mitigate the chatter dynamics with input saturations. To guarantee the feasibility of the proposed approach, moderate stable conditions of the closed‐loop system are afterwards derived by using the LaSalle–Yoshizawa theorem as well. Finally, numerical simulations are conducted to show the substantially enlarged stable region in the Lobe Diagram. Thus, the method can be expected to improve the efficiency of milling processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive actuator failure compensation for multivariable feedback linearizable systems

A feedback linearization‐based adaptive control scheme is developed for multivariable nonlinear systems with redundant actuators subject to uncertain failures. Such an adaptive controller contains a direct adaptive actuator failure compensator to compensate the uncertain actuator failure, a nonlinear feedback to linearize the nonlinear dynamics, and a linear feedback to stabilize the linearized system. The key new design feature is the estimation of both the failure patterns and the failure values, for direct adaptive actuator failure compensation, newly developed for multivariable feedback linearizable nonlinear systems. With direct control signal adaptation, the adaptive failure compensation design ensures closed‐loop stability and asymptotic output tracking in the presence of actuator failure uncertainties. Simulation results from an application to attitude control of a near‐space vehicle dynamic model are presented to verify the desired system performance with adaptive actuator failure compensation. Copyright © 2015 John Wiley & Sons, Ltd.     

A projection-based decomposition for the scalability of evolvable hardware

Scalability is a main and urgent problem in evolvable hardware (EHW) field. For the design of large circuits, an EHW method with a decomposition strategy is able to successfully find a solution, but requires a large complexity and evolution time. This study aims to optimize the decomposition on large-scale circuits so that it provides a solution for the EHW method to scalability and improves the efficiency. This paper proposes a projection-based decomposition (PD), together with Cartesian genetic programming (CGP) as an EHW system namely PD-CGP, to design relatively large circuits. PD gradually decomposes a Boolean function by adaptively projecting it onto the property of variables, which makes the complexity and number of sub-logic blocks minimized. CGP employs an evolutionary strategy to search for the simple and compact solutions of these sub-blocks. The benchmark circuits from the MCNC library, \(n\)-parity circuits, and arithmetic circuits are used in the experiment to prove the ability of PD-CGP in solving scalability and efficiency. The results illustrate that PD-CGP is superior to 3SD-ES in evolving large circuits in terms of complexity reduction. PD-CGP also outperforms GDD+GA in evolving relatively large arithmetic circuits. Additionally, PD-CGP successfully evolves larger \(n\)-even-parity and arithmetic circuits, which have not done by other approaches.     

Upper Bounds on Number of Steals in Rooted Trees

Inspired by applications in parallel computing, we analyze the setting of work stealing in multithreaded computations. We obtain tight upper bounds on the number of steals when the computation can be modeled by rooted trees. In particular, we show that if the computation with n processors starts with one processor having a complete k-ary tree of height h (and the remaining n ? 1 processors having nothing), the maximum possible number of steals is \({\sum }_{i=1}^{n}(k-1)^{i}\binom {h}{i}\).     

Set-based particle swarm optimization with status memory for knapsack problem

Set-based particle swarm optimization (S-PSO) operates on discrete space. S-PSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In S-PSO, a velocity is a set with possibility and a position is a candidate solution. In this paper, we present a novel algorithm of set-based particle swarm optimization with status memory (S-PSOSM) to decide the position based on the previous position for solving knapsack problem. Some operators are redefined for S-PSOSM. S-PSOSM is a simple algorithm because the state of probability reduces. In addition, the weight of S-PSOSM is discussed. S-PSOSM shows high qualities in experimental results.     

Quantum image encryption based on generalized affine transform and logistic map

Quantum circuits of the generalized affine transform are devised based on the novel enhanced quantum representation of digital images. A novel quantum image encryption algorithm combining the generalized affine transform with logistic map is suggested. The gray-level information of the quantum image is encrypted by the XOR operation with a key generator controlled by the logistic map, while the position information of the quantum image is encoded by the generalized affine transform. The encryption keys include the independent control parameters used in the generalized affine transform and the logistic map. Thus, the key space is large enough to frustrate the possible brute-force attack. Numerical simulations and analyses indicate that the proposed algorithm is realizable, robust and has a better performance than its classical counterpart in terms of computational complexity.     

基于LabVIEW的显微镜自动控制设计

为方便CCD相机采集显微镜下的图像,对显微镜的控制进行了研究;设计了一种实现显微镜自动控制的方法;利用THB6128芯片驱动步进电机实现焦距的电控调节,利用PT4115芯片控制LED灯实现照明灯光亮暗的调节,基于LabVIEW虚拟仪器平台开发主控制程序搭建外围硬件,实现显微镜的自动控制;实验证明,上位机运用程序通过串口进行数据通信向下位机发送指令,通过调节LED灯的亮暗以及步进电机转动带动载物台的上下移动,实现了在一个合适的光照和焦距下获取清晰的图像;使显微镜控制更加的简化与精确,便于图像的采集。     

基于OMAP3530嵌入式最小系统的开发

随着嵌入式系统日趋复杂,类似机载状态监测系统,对嵌入式处理器在高性能计算和复杂控制方面的性能提出了更高的要求;针对复杂嵌入式系统的高性能需求,介绍了TI公司ARM+DSP架构的双核异构处理器OMAP3530,并进行了OMAP3530嵌入式最小系统的开发,包括硬件、软件设计两个方面;硬件设计包括电源、时钟、存储器以及外围接口等模块,实现了OMAP3530启动以及和外围通信的最基本硬件组成;软件设计包括ARM端操作系统移植、ARM和DSP双核通信,在此基础上设计了双核的应用程序;最后采用LabVIEW在上位机上设计了软件部分的测试程序,测试了系统的完整性;OMAP3530作为一款高性能的嵌入式处理器,为复杂的嵌入式系统应用提供了解决思路。     

光伏微逆变器电流传感器和功率管开路故障诊断

当电流传感器出现性能蜕化、故障或失效时,光伏微逆变器系统的输出会受到严重影响,甚至微逆变器系统其他部件有可能被直接损坏而导致整个系统永久失效;微逆变器系统中反激式变换器功率管的开路故障会引起2个交错支路电流不平衡,导致输出电流波形畸变率变大.为此,提出一种基于状态观测器的光伏微逆变器电流传感器和功率管开路故障诊断方法.建立两路反激式变换器的数学模型;构建状态观测器以实现对两路反激式变换器原边电流的在线估计,并生成残差;将残差与阈值进行比较,实现对微逆变器系统中电流传感器与功率管的实时故障诊断.仿真结果验证该方法可行且有效.