Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

共网数字集群系统应用问题的研究

现今国内的数字集群网络发展存在局限性、差异性，还远没有达到“网”状分布的程度，因此，共网数字集群发展空间巨大、前景广阔。通过列举共网数字集群系统在龙嘉国际机场和长春雷锋车队的成功应用案例，探讨了我国共网数字集群系统应用的可行性和必要性。     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Delay compensated control of the Stefan problem and robustness to delay mismatch

This paper presents a control design for the one‐phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid‐solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first‐order hyperbolic partial differential equation (PDE), resulting in a cascaded transport‐diffusion PDE system defined on a time‐varying spatial domain described by an ordinary differential equation (ODE). Two nonlinear backstepping transformations are utilized for the control design. The setpoint restriction is given to guarantee a physical constraint on the proposed controller for the melting process. This constraint ensures the exponential convergence of the moving interface to a setpoint and the exponential stability of the temperature equilibrium profile and the delayed controller in the norm. Furthermore, robustness analysis with respect to the delay mismatch between the plant and the controller is studied, which provides analogous results to the exact compensation by restricting the control gain.     

Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

WKB近似下的Fourier衍射成象方法

对于介质目标微波衍射成象，本文引入了ＷＫＢ近似来模拟目标内部总场。基于这种近似，我们导出了Ｆｏｕｒｉｅｒ衍射公式，并采用了广义滤波逆传播方法由目标空间谱实现目标特性的重建。计算机模拟结果表明采用ＷＫＢ近似重建目标特性较Ｂｏｒｎ近似有明显改善。     

一种新的机器人手臂控制方法

从机器人手臂的关节电机力学出发，本文提出了一种独立于现行机器人关节控制器的离线补偿方法，通过对－２自由度机器人的数值研究，证明该法不仅能有效地克服由于惯性负载，关节间耦合与重力效应给控制系统带来的动态精度问题，而且还可以消除由于控制系统本身的固有特性所决定的系统的跟踪误差。     

基于小波算法的摆式列车倾摆指令实时提取

由于摆式列车线路检测系统测得的线路超高时变率信号是平稳的且含有幅度大、频带宽的噪声 ,难以用常规的滤波方法得到摆式列车实时倾摆指令。本文介绍了多分辨率分析的基本原理及快速算法 ,讨论了基函数的选取 (构造 )原则。根据超高时变率信号的特征 ,合理选择基函数 ,提出了一种对流式数据的实时滤波算法 ,通过对仿真和线路试验实测数据的处理与常规滤波方法进行了比较。结果表明 ,该算法能更快地实时提取摆式列车倾摆指令。     

四种国民常用饮水中非挥发性有机物及其致突变活性的比较研究

比较我国居民常用饮水种类自来水、净化水(自来水经净水器过滤)、凉开水(自来水经煮沸后冷却)、纯净水(自来水经以反渗透为主的多重工艺处理)的非挥发性有机物(NOP)污染状况及其致突变活性。结果表明,四种水中检测到的NOP种类分别为自来水39种,净化水40种,凉开水20种,纯净水8种;毛细色谱显示的NOP总丰面积值依次为5.62×109,5.57×109,2.65×109,1.87×109。四种水的移码型及碱基置换型致突变活性依次为:自来水>净化水>凉开水>纯净水,其中自来水在相当1L、2L、4L水量的剂量均为阳性致突变活性,而纯净水在同样的剂量均为阴性。