Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

Least-squares integration of one-dimensional codistributions with application to approximate feedback linearization

We study the problem of approximating one-dimensional nonintegrable codistributions by integrable ones and apply the resulting approximations to approximate feedback linearization of single-input systems. The approach derived in this paper allows a linearizable nonlinear system to be found that is close to the given system in a least-squares (L ₂) sense. A linearly controllable single-input affine nonlinear system is feedback linearizable if and only if its characteristic distribution is involutive (hence integrable) or, equivalently, any characteristic one-form (a one-form that annihilates the characteristic distribution) is integrable. We study the problem of finding (least-squares approximate) integrating factors that make a fixed characteristic one-form close to being exact in anL ₂ sense. A given one-form can be decomposed into exact and inexact parts using the Hodge decomposition. We derive an upper bound on the size of the inexact part of a scaled characteristic one-form and show that a least-squares integrating factor provides the minimum value for this upper bound. We also consider higher-order approximate integrating factors that scale a nonintegrable one-form in a way that the scaled form is closer to being integrable inL ₂ together with some derivatives and derive similar bounds for the inexact part. This allows a linearizable nonlinear system that is close to the given system in a least-squares (L ₂) sense together with some derivatives to be found. The Sobolev embedding techniques allow us to obtain an upper bound on the uniform (L _∞) distance between the nonlinear system and its linearizable approximation. This research was supported in part by NSF under Grant PYI ECS-9396296, by AFOSR under Grant AFOSR F49620-94-1-0183, and by a grant from the Hughes Aircraft Company.     

实施取水定额管理的几个关键问题探讨

通过对全国23个省级单位出台的用水定额标准进行分析，指出目前定额管理存在6个主要问题：一是概念模糊，二是制定方法不统一、不规范，三是定额标准体系不完善，四是可操作性较差，五是计量系统不完善，六是缺乏取水定额管理信息化平台。提出应采用“取水定额”这一表述，并提出了取水定额的体系，包括基础计量体系、定额制定体系、信息链体系、定期更新体系4部分。明确了取水定额管理体系建设主要内容应包括：法律法规体系、定额制定体系、水价管理体系、信息通道体系。     

试论企业人格化管理的力量因素

论述了影响企业人格化管理的力量因素，并指出制度纪律是其保障因素，道德规范是其自律因素，理想目标是其进取因素。     

提高钢水质量减少铸件气孔

通过规范冶炼的操作，加强冶炼过程控制，细化分解技术指标，制定奖励方案，提高了钢水质量，解决了铰链梁铸件的气孔问题。     

一类线性时变群体系统稳定性的代数判据

针对在判断群体系统的稳定性时没有一般的方法和程序构造Lyapunov函数这个难点,利用矩阵范数,孤立子系统的矩阵指数函数与比较原理提出了一类线性时变群体系统平凡解一致稳定,所有解一致有界的充分条件。方便此类群体系统的稳定性分析,为研究其他群体系统稳定性的代数判据提供了理论基础。可以在此基础上,进一步研究一类非线性群体系统稳定性的代数判据。同时,还给出了具体算例,说明所提方法的正确性。此代数判据应用简便,灵活,适于实际应用。     

学术自由与学术规范

学术自由是学术形成与发展的必要条件，已有的学术规范又为新的学术提供了对象与基础。二者对学术具有同样重要的意义。学术是自由探索与遵循规范的矛盾与辩证统一。     

A continuous-time framework for least squares parameter estimation

This paper proposes a continuous-time framework for the least-squares parameter estimation method through evolution equations. Nonlinear systems in the standard state space representation that are linear in the unknown, constant parameters are investigated. Two estimators are studied. The first one consists of a linear evolution equation while the second one consists of an impulsive linear evolution equation. The paper discusses some theoretical aspects related to the proposed estimators: uniqueness of a solution and an attractive equilibrium point which solves for the unknown parameters. A deterministic framework for the estimation under noisy measurements is proposed using a Sobolev space with negative index to model the noise. The noise can be of large magnitude. Concrete signals issued from an electronic device are used to discuss numerical aspects.     

广义Mamdani模糊系统依K-积分模的泛逼近及其实现过程

首先,通过引入拟减法算子给出K-积分模定义,并针对广义Mamdani模糊系统实施等距剖分其输入空间. 其次,应用分片线性函数（Piecewise linear function,PLF）的性质构造性地证明了广义Mamdani模糊系统在K-积分模意义下具有泛逼近性,从而将该模糊系统对连续函数空间的逼近能力扩展到一类可积函数类空间上. 最后,通过模拟实例给出该广义Mamdani模糊系统对给定可积函数的泛逼近及实现过程.