Indirect adaptive control of nonlinear system via dynamic multilayer neural networks with multi‐time scales

This paper deals with adaptive nonlinear identification and trajectory tracking problem via dynamic multilayer neural network with different time scales. By means of a Lyapunov‐like analysis, we determine stability conditions for the on‐line identification. Then, a sliding mode controller is designed for trajectory tracking with consideration of the modeling error and disturbance. The main contributions of the paper lie in the following aspects. First, we extend our prior identification results of single‐layer dynamic neural networks with multi‐time scales to those of multilayer case. Second, the e‐modification in standard use in adaptive control is introduced in the on‐line update laws to guarantee bounded weights and bounded identification errors. Third, the potential singularity problem in controller design is solved by using new update laws for the NN weights so that the control signal is guaranteed bounded. The stability of proposed controller is proved by using Lyapunov function. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal robust optimization approximation for chance constrained optimization problem

Chance constraints are useful for modeling solution reliability in optimization under uncertainty. In general, solving chance constrained optimization problems is challenging and the existing methods for solving a chance constrained optimization problem largely rely on solving an approximation problem. Among the various approximation methods, robust optimization can provide safe and tractable analytical approximation. In this paper, we address the question of what is the optimal (least conservative) robust optimization approximation for the chance constrained optimization problems. A novel algorithm is proposed to find the smallest possible uncertainty set size that leads to the optimal robust optimization approximation. The proposed method first identifies the maximum set size that leads to feasible robust optimization problems and then identifies the best set size that leads to the desired probability of constraint satisfaction. Effectiveness of the proposed algorithm is demonstrated through a portfolio optimization problem, a production planning and a process scheduling problem.     

模拟3种有机膦系阻垢剂与方解石(104)面的相互作用

通过pH曲线实验研究了乙二胺四亚甲基膦酸(EDTMP),己二胺四亚甲基膦酸(HDTMP)和二乙烯三胺五亚甲基膦酸(DTPMP)对碳酸钙垢的阻垢性能,在相同的加药浓度下阻垢性能强弱顺序为:DTPMPEDTMPHDTPM。同时采用周期性边界条件下的分子动力学方法,模拟研究了在水分子存在条件下各阻垢剂与方解石(104)面的相互作用,得到了相应的结合能和原子间距离等参数。结果表明:阻垢分子膦酸基团中的双键氧与碳酸钙中的Ca~(2+)形成的强静电相互作用力对吸附起了主导作用,同时膦酸基团中的氢与晶面中的氧形成了氢键,加强了吸附效果。综合考虑各分子在晶面(104)上的吸附效果,其结果与实验相符合;从分子中膦酸基团作用个数也可看出,HDTMP只有一个膦酸基团靠近晶面,因此作用力也是最弱的。     

Spectral Animation Compression

This paper presents a spectral approach to compress dynamic animation consisting of a sequence of homeomor-phic manifold meshes. Our new approach directly compresses the field of deformation gradient d...     

Mathematical representation of radiality constraint in distribution system reconfiguration problem

Distribution systems are most commonly operated in a radial configuration for a number of reasons. In order to impose radiality constraint in the optimal network reconfiguration problem, an efficient algorithm is introduced in this paper based on graph theory. The paper shows that the normally followed methods of imposing radiality constraint within a mixed-integer programming formulation of the reconfiguration problem may not be sufficient. The minimum-loss network reconfiguration problem is formulated using different ways to impose radiality constraint. It is shown, through simulations, that the formulated problem using the proposed method for representing radiality constraint can be solved more efficiently, as opposed to the previously proposed formulations. This results in up to 30% reduction in CPU time for the test systems used in this study.     

Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

Sensor interpixel correlation analysis and reduction for color filter array high dynamic range image reconstruction

High dynamic range imaging (HDRI) by bracketing of low dynamic range (LDR) images is demanding, as the sensor is deliberately operated at saturation. This exacerbates any crosstalk, interpixel capacitance, blooming and smear, all causing interpixel correlations (IC) and a deteriorated modulation transfer function (MTF). Established HDRI algorithms exclude saturated pixels, but generally overlook IC. This work presents a calibration method to estimate the affected region from saturated pixels for a color filter array (CFA) sensor, using the native CFA as a matched filter. The method minimizes color crosstalk given a set of candidates for proximity regions, and requires no special setup. Results are shown for a 21‐bit HDR output image with improved color fidelity and reduced noise. The calibration reduces IC in the LDR images and is performed only once for a given sensor. The improvement is applicable to any HDRI algorithm based on CFA image bracketing, irrespective of sensor technology. Generalizations to subsaturated and supersaturated pixels are described, facilitating a suggested irradiance‐exposure dependent point spread function charge repatriation strategy.     

Adaptive control for switched uncertain nonlinear systems with time‐varying output constraint and input saturation

This paper is concerned with adaptive tracking control for switched uncertain nonlinear systems, which contain the time‐varying output constraint (TVOC) and input asymmetric saturation characteristic. In response to the unknown functions, the fuzzy logic systems are adopted. The controller is constructed by the backstepping technique. Based on the Tangent Barrier Lyapunov Function (BLF‐Tan), an adaptive switched control scheme is designed. It is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded with TVOC under arbitrary switchings. Furthermore, the effectiveness of presented control method is validated via the simulation example.     

Extended-state-observer-based dynamic surface control of flexible-joint robot systems with input saturation

This article presents an extended-state-observer-based dynamic surface control approach for flexible-joint robot systems with asymmetric input saturation and large unknown dynamic knowledge. Traditional controllers for flexible-joint robot systems usually use approximation technology to deal with unknown dynamics knowledge. Unlike the traditional control algorithm, this article utilizes an extended state observer to estimate the unknown dynamics. For the closed-loop system, the delay strategy handles the time-scale separation issue, the filtering system overcomes the “explosion of differentiation” caused by the repeated differentiation of auxiliary control signals, and the mean-value-theorem solves the input saturation problem of the actuator. The stability analysis implies that estimation errors of extended state observers (ESOs) and other state variables are semiglobally uniformly ultimately bounded. Compared with fuzzy control algorithms, the novel ESO-based dynamic surface control approach not only omits online learning time but also uses only a few control parameters to obtain satisfactory tracking performance. Finally, a comparison simulation experiment is provided to illustrate the effectiveness of the gained conclusions.     

Dynamic viscoelasticity and molecular orientation in uniaxially drawn PC/PET blends

The dependence of dynamic viscoelasticity on molecular orientation of the hot-drawn polycarbonate (PC)/poly(ethylene terephthalate) blends was studied experimentally. The oriented states of samples were investigated by wide-angle X-ray diffraction and quantified by Hermans' factor. The viscoelasticity was probed by dynamic mechanical analysis. For the fitting curves of dynamic modulus versus orientation, the PC-rich blends with different compositions had an opposite concavity and convexity compared with the neat PC. The difference revealed the influence of molecular mobility on orientation and viscoelasticity. The assumption on the phase morphological change from sea-island to local sandwich-like structure in blends was proposed and used to interpret the variation of slope of fitting curves. The relationship between orientation and viscoelasticity was observed in PC-rich blends, which can help understand the mechanism of molecular orientation and develop the constitutive relations for simulation. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47514.