M‐matrices and global convergence of discontinuous neural networks

The paper considers a general class of neural networks possessing discontinuous neuron activations and neuron interconnection matrices belonging to the class of M‐matrices or H‐matrices. A number of results are established on global exponential convergence of the state and output solutions towards a unique equilibrium point. Moreover, by exploiting the presence of sliding modes, conditions are given under which convergence in finite time is guaranteed. In all cases, the exponential convergence rate, or the finite convergence time, can be quantitatively estimated on the basis of the parameters defining the neural network. As a by‐product, it is proved that the considered neural networks, although they are described by a system of differential equations with discontinuous right‐hand side, enjoy the property of uniqueness of the solution starting at a given initial condition. The results are proved by a generalized Lyapunov‐like approach and by using tools from the theory of differential equations with discontinuous right‐hand side. At the core of the approach is a basic lemma, which holds under the assumption of M‐matrices or H‐matrices, and enables to study the limiting behaviour of a suitably defined distance between any pair of solutions to the neural network. Copyright © 2006 John Wiley & Sons, Ltd.     

永磁直线同步电动机改进全局滑模变结构控制研究

针对滑模控制永磁直线同步电动机（PMLSM）不能实现有限时间控制以及全局滑模控制（GSMC）不能实现快速收敛的问题,提出了一种改进型GSMC算法来设计直线伺服速度控制器。该算法采用了由非线性项、线性项相结合的动态滑模面以及等速趋近律,非线性滑模面衰减函数由3个指数函数项组成一阶可导函数, 并能在有限时间内衰减为零。仿真结果表明,改进GSMC不仅使系统具有全局鲁棒性,且能在保证高跟踪精度的同时加快响应速度和抗干扰能力。     

Parallel FETI‐DP algorithm for efficient simulation of large‐scale EM problems

An efficient parallelization of the dual‐primal finite‐element tearing and interconnecting (FETI‐DP) algorithm is presented for large‐scale electromagnetic simulations. As a nonoverlapping domain decomposition method, the FETI‐DP algorithm formulates a global interface problem, whose iterative solution is accelerated with a solution of a global corner problem. To achieve a good load balance for parallel computation, the original computational domain is decomposed into subdomains with similar sizes and shapes. The subdomains are then distributed to processors based on their close proximity to minimize inter‐processor communication. The parallel generalized minimal residual method, enhanced with the iterative classical Gram‐Schmidt orthogonalization scheme to reduce global communication, is adopted to solve the global interface problem with a fast convergence rate. The global corner‐related coarse problem is solved iteratively with a parallel communication‐avoiding biconjugate gradient stabilized method to minimize global communication, and its convergence is accelerated by a diagonal preconditioner constructed from the coarse system matrix. To alleviate neighboring communication overhead, the non‐blocking communication approach is employed in both generalized minimal residual and communication‐avoiding biconjugate gradient stabilized iterative solutions. Three numerical examples are presented to demonstrate the accuracy, scalability, and capability of the proposed parallel FETI‐DP algorithm for electromagnetic modeling of general objects and antenna arrays. Copyright © 2016 John Wiley & Sons, Ltd.     

An H∞ approach to linear iterative learning control design

A new design methodology for iterative learning control systems is developed. It is based on the convergence condition for systems operating on an infinite time interval which is of the H_∞ type. The principal idea of the design technique is to design a learning controller such that the speed of convergence is maximized, with a compromise to robustness. The issue of finite versus infinite trial lengths is addressed, as well as limitations on the best achievable rate of convergence due to structural properties of the plant.     

提高APF谐波补偿能力的全局快速Terminal滑模控制

谐波补偿环节的谐波电流跟踪控制是衡量有源电力滤波器(APF)性能优劣的关键因素之一。针对常规滑模控制中,无论如何调整线性滑模面参数都无法使得跟踪误差在有限时间内收敛到零的问题,提出了电流环基于全局快速Terminal滑模的谐波电流跟踪控制策略。该方法在线性滑模面的基础上引入非线性函数,弥补了常规滑模控制只能实现状态渐进收敛的缺点,在提高滑模控制瞬态性能的同时,消除了切换项,从本质上削弱了抖振。在不改变谐波检测环节的条件下,对APF进行稳态和暂态性能测试,将文中提出的全局快速Terminal滑模控制与常规指数趋近律的滑模控制对比,验证了文中控制策略的正确性和有效性。     

Unknown piecewise constant parameters identification with exponential rate of convergence

The scope of this research is the identification of unknown piecewise constant parameters of linear regression equation under the finite excitation condition. Compared to the known methods, to make the computational burden lower, only one model to identify all switching states of the regression is used in the developed procedure with the following two-fold contribution. First of all, we propose a new truly online estimation algorithm based on a well-known DREM approach to detect switching time and preserve time alertness with adjustable detection delay. Second, despite the fact that a switching signal function is unknown, the adaptive law is derived that provides global exponential convergence of the regression parameters estimates to their true values in case the regressor is finitely exciting somewhere inside the time interval between two consecutive parameters switches. The robustness of the proposed identification procedure to the influence of external disturbances is analytically proved. Its effectiveness is demonstrated via numerical experiments, in which both abstract regressions and a second-order plant model are used.     

Generalized forgetting functions for on‐line least‐squares identification of time‐varying systems

The problem of on‐line identification of a parametric model for continuous‐time, time‐varying systems is considered via the minimization of a least‐squares criterion with a forgetting function. The proposed forgetting function depends on two time‐varying parameters which play crucial roles in the stability analysis of the method. The analysis leads to the consideration of a Lyapunov function for the identification algorithm that incorporates both prediction error and parameter convergence measures. A theorem is proved showing finite time convergence of the Lyapunov function to a neighbourhood of zero, the size of which depends on the evolution of the time‐varying error terms in the parametric model representation. Copyright © 2001 John Wiley & Sons, Ltd.     

实时无功优化调度中的邻域搜索改进遗传算法

为了避免遗传算法的早熟收敛及改善其收敛性能，提出了电力系统最优无功调度和电压控制的一种改进遗传算法。算法中采用了分组整数编码技术和锦标赛选择机制；结合十进制整数编码的特点，提出了邻近变异的操作算子，避免了二进制编码中的海明悬崖(Hamming cliffs)；在遗传迭代结束后再引入邻域搜索技术，以极短的时间完成搜索。将此算法应用在海南电网的实时无功优化调度中，结果表明该算法能迅速获得全局优化解，具有很好的全局收敛性能，能满足电力系统无功优化实时调度的要求。     

Second‐order blind algorithms for adaptive recursive linear equalizers: analysis and lattice implementation

Adaptive recursive linear equalizers present important advantages in terms of performance and robustness compared to more standard finite impulse response structures, and provide a means for blindly initializing the decision feedback structure. We present an analysis of a pair of algorithms for the adaptation of the recursive part of the equalizer, which are based on the second‐order statistics of the received signal, in a multichannel complex‐valued setting with spatially coloured noise. When the number of equalizer poles is no less than the channel order, both algorithms enjoy a unique stationary point, which in addition is locally convergent; global convergence properties, on the other hand, can be quite different. When the optimum setting presents poles close to the stability boundary, the lattice structure is preferred for ease of stability monitoring. Lattice versions of the two algorithms are developed and their convergence properties discussed. Copyright © 2006 John Wiley & Sons, Ltd.     

Global partially decentralized adaptive stabilization of discrete-time systems

It is shown in this paper that the inclusion of a ‘centralized’ normalization signal in an otherwise decentralized adaptive control scheme is sufficient to ensure global convergence for a well-defined class of interconnections. The latter is characterized by a frequency domain condition on the best attainable transfer matrix for the given controller structure. Our main contributions are that we circumvent the need for ‘sufficiently weak’ interconnection assumptions that prevails in the available literature and provide for the first time rigorous conditions for global convergence instead of just signal boundedness.     

基于全局滑模时滞的电力系统混沌振荡控制

电力系统易受扰动影响,在一定扰动条件下会进入混沌状态。通过分岔图和李雅普诺夫指数谱分析了扰动Pe与Pk单独作用与共同作用时对电力系统的影响,当Pe与Pk单独作用时,系统状态均随着扰动的增加由周期态过渡到混沌态,当Pe与Pk共同作用时,系统状态均随着扰动的增加由混沌态过渡到周期态再过渡到混沌态。设计了一种全局滑模时滞控制策略,时滞控制采用延时反馈环节,即误差信号中采用上个采样周期的采样值与此时的采样值来对不确定系统项与扰动项进行估计,但由于延时环节存在时滞误差,导致系统收敛速度较慢且扰动抑制能力较差。为此,将时滞控制与全局滑模控制相结合,并设计具有快速收敛特性的时滞补偿项,提高系统收敛速度与抗扰动能力,并且可以抑制上界未知的外部扰动。仿真结果表明,相较于时滞控制,所设计的全局滑模时滞控制收敛速度更快,超调量更小,在系统遭受周期扰动与阶跃扰动时仍能保证收敛。     

A numerically stable,finite memory,fast array recursive least squares filter for broadband active noise control

For broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast‐array Kalman filter, which uses rotation matrices to calculate the filter parameters. However, when this algorithm is implemented, it can show unstable behavior because of finite precision error propagation. In this paper, a novel algorithm is presented, which exhibits the fast convergence and tracking properties and the linear calculation complexity of the fast‐array Kalman filter but does not suffer from the mentioned numerical problems. This is accomplished by running two finite length growing memory recursive least squares filters in parallel and using a convex combination of the two filters when the control signal is calculated. A reset of the filter parameters with proper re‐initialization is enforced periodically. The mixing parameters will be chosen in such a way that the total available information used for the calculation of the control signal will be approximately equal at every time instance. The performance of the filter is shown in numerical simulations and real‐time lab experiments. The numerical experiments show that the algorithm performs better numerically than the fast‐array sliding window recursive least squares filter, while achieving a comparable convergence rate and tracking performance. The real‐time lab experiments confirm the behavior shown in the simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

Global adaptive finite‐time stabilization of a class of switched nonlinear systems with parametric uncertainty

This paper investigates the global adaptive finite‐time stabilization of a class of switched nonlinear systems, whose subsystems are all in p (p≤1) normal form with unknown control coefficients and parametric uncertainties. The restrictions on the power orders and the nonlinear perturbations are relaxed. By using the parameter separation technique, the uncertain parameters are separated from nonlinear functions. A systematic design procedure for a common state feedback controller and a switching adaptive law is presented by employing the backstepping methodology. It is proved that the closed‐loop system is finite‐time stable under arbitrary switching by utilizing the common Lyapunov function. Finally, with the application to finite‐time control of chemical reactor systems, the effectiveness of the proposed method is demonstrated. Copyright © 2015 John Wiley & Sons, Ltd.     

改进量子进化混合优化算法在溪洛渡电站机组组合中的应用研究

传统方法求解水电站机组组合问题时存在易陷入局部最优、易出现"维数灾"、收敛性差等缺陷,因此提出了一种改进量子进化混合优化算法用以解决这一问题。通过将量子进化算法与基于经济运行总表的动态规划法嵌套,分别对外层机组组合和内层负荷分配问题进行迭代优化;同时,引入最短开、停机时间修补策略和备用容量修补策略,有效处理多重复杂约束,在保证计算精度的前提下,显著提高收敛速度。以溪洛渡电站经济运行中的机组组合问题为工程背景进行了实例研究,并与已有DP和IBPSO方法进行对比分析,结果显示所提算法简单高效,优化效果好,具有较强的工程实用性。     

A uniformly stable conformal FDTD‐method in Cartesian grids

A conformal finite‐difference time‐domain algorithm for the solution of electrodynamic problems in general perfectly conducting 3D geometries is presented. Unlike previous conformal approaches it has the second‐order convergence without the need to reduce the maximal stable time step of conventional staircase approach. A novel proof for the local error rate for general geometries is given, and the method is verified and compared to other approaches by means of several numerical 2D examples. Copyright © 2003 John Wiley & Sons, Ltd.     

基于改进遗传算法的堆石体流变模型参数反馈分析

本文提出一种序列二次规划优化算法与标准遗传算法结合的流变模型参数反馈分析方法,这种算法既发挥了序列二次规划优化算法省时、高效、局部搜索能力强的特点,又发挥了遗传算法可以搜索到全局最优解而避免陷入局部极小值的优点,改善了常规遗传算法的收敛速度。将遗传算法搜索到的全局最优近似解作为初始值,代入收敛效率较高的序列二次规划程序进行最终局部优化。以某堆石坝为例,应用上述反演方法对高围压下的堆石体9参数流变模型参数进行了反演分析,验证了此方法的可行性与有效性。     

New solutions to the 2D adaptive visual servoing problem with relaxed excitation requirements

In this paper, we present three new globally convergent vision‐based position controllers for a planar manipulator in a fixed‐camera configuration, where the camera orientation and scale factor are considered unknown. This is a basic adaptive visual servoing problem whose solution was hampered by the nonlinear dependence of the system dynamics on the unknown parameters. Proposing a suitable reparameterization of the systems mathematical model, and exploiting some structural properties of it, we propose three different solutions to the problem. The first one is the certainty equivalent version of the known parameter controller and requires some excitation conditions to ensure global asymptotic convergence. A second version of the controller, which is now slightly more complicated and, possibly, needs to inject some high gain but requires significantly weaker excitation conditions, is given. Finally, we propose a slight modification to the second scheme to achieve the trajectory tracking in finite time. The efficacy of the three adaptive controllers is shown through realistic simulations.     

一种高效光伏多峰MPPT控制算法

在局部阴影条件下,光伏阵列的输出功率会出现多峰现象,传统MPPT控制方法搜索全局最大功率点会发生寻优失效。提出了一种高效的光伏多峰MPPT控制算法。该算法基于天牛须搜索算法,通过引入随时间变化的自适应步长因子,在算法初期自动的选取较大的搜索步长,使之保持较高的全局搜索能力;中期逐渐增大步长的衰减速度,加快算法收敛;后期逐渐减小步长的衰减速度,以提高收敛精度。Matlab结果表明,该算法可有效地减小搜索时间和搜索震荡,显著提高收敛速度,同时又可大大地提高搜索精度,准确搜索到光伏最大输出功率。     

基于混合积分终端滑模的超级电容有限时间平抑电压波动方法

提出一种基于混合积分终端滑模的超级电容平抑电压波动方法,提高直流母线电压的收敛速度和抗干扰性。利用有限时间控制手段,引入最终吸引子,设计超级电容滑模面中的误差积分项为误差积分和带有分数幂误差积分线性组合的混合积分项,并证明这种混合积分滑模面具有有限时间收敛性能。仿真表明,基于混合积分终端滑模控制方法的超级电容平抑电压波动方法具有更快的收敛速度和更强的抗干扰性能,保证直流母线在有限时间内稳定。     

Fixed time synchronization of delayed chaotic neural networks by using active adaptive control

This article aims to investigate the fixed time synchronization of a class of chaotic neural systems by way of adaptive control method. Using Lyapunov stability theory, a new fixed time stability theorem which plays an important role on the synchronization scheme is presented at first. Then, combining the fixed time stability theorem and adaptive control technique, an adaptive control scheme has been developed to achieve the fixed time synchronization of chaotic neural systems. The proposed controllers assure the global convergence of the error dynamics in fixed-time based on the Lyapunov stability theory. Furthermore, the proposed control strategy cannot only provide a fast convergence rate, but also afford a bounded convergence time which is unrelated to the initial values and easy to work out by using the simple time calculation formula. Finally, numerical simulations are presented by taking a typical two-order chaotic neural system as an example to verify and demonstrate the effectiveness of the proposed scheme.