具有量化误差的多步长非线性采样系统的镇定

该文研究一类非线性控制系统在采样器采样过程中产生量化误差的情况下多步长采样镇定问题. 运用近似DTD方法, 在非线性系统的近似离散时间模型上设计全局状态反馈镇定控制器. 当系统近似误差和采样量化误差被限制在一定的条件下, 可以得到含量化误差的多步长非线性采样系统是半全局实用渐近稳定. 最后, 仿真例子验证了所得结果的有效性.     

高维带宽有限随机信号从平均过采样的指数阶逼近

本文中我们主要考虑利用有限的平均过采样值来重构高维带宽有限随机信号.我们给出了一个能够达到指数阶衰减逼近能力的重构算法.对于一般型和乘积型的采样测度,我们分别给出了对应的重构算法和指数阶衰减的重构误差估计.     

带宽有限随机过程从过采样点的指数阶逼近

带宽有限的宽平稳随机过程的Shannon采样定理在1957年被建立起来.从那以后,关于它在其他随机过程的推广有广泛的研究.然而,直接截断Shannon级数收敛较慢.特别地,我们知道利用在Nyquist采样率下得到的n个采样点的截断级数的均方逼近误差的收敛速率是O(1/n~(1/2)).本文我们n考虑用有限的过采样点来重构带宽有限宽平稳随机过程,其中过采样点是指连续两个采样点之间的距离小于Nyquist采样率.我们研究了最优的线性重构算法和与其相关的本性逼近误差阶.通过过采样,我们发现线性重构算法可以达到指数阶衰减逼近,并且我们还证明线性重构算法不可能有快于指数阶的衰减速率.另外,我们还构造了两个具体的指数阶衰减的重构算法.     

事件触发下混合时滞神经网络的状态估计

研究了事件触发机制下混合时滞神经网络的状态估计问题.通过引入依赖于测量输出且具有指数衰减特性的阈值函数,设计了新的事件触发机制来降低采样和通信频率.综合混合时延和事件触发特性,建立了新的状态估计误差系统.采用Lyapunov函数和不等式技术,建立了误差系统指数稳定性条件,分析并排除了事件触发机制中的Zeno现象.最后通过例子验证了理论方法的有效性.     

Sampling Consensus of 2nd-Order Multi-Agent Systems Based on Time-Varying Topology北大核心CSCD

基于速度一致位移差保持不变的一致性概念,研究了二阶多智能体系统在时变拓扑下的采样一致性问题。首先,引入虚拟领导者,将具有时变拓扑结构的多智能体系统的采样一致性问题转换为误差系统的采样控制稳定性问题。其次,通过预估采样误差,研究采样误差对系统达到一致性的影响。最后,应用Lyapunov稳定性理论,分析所构造的误差系统的稳定性,并给出该误差系统最终稳定的充分条件。数值仿真结果验证了理论分析的有效性和正确性。     

一类线性时滞系统的采样数据控制

研究了线性时滞系统的采样数据控制问题.基于新的依赖时间的LyapunovKrasovskii泛函,采用广义系统方法与自由权矩阵方法,得到了采样数据控制的指数稳定性分析和状态反馈控制器设计的条件,并表达为线性矩阵不等式形式.通过仿真举例,证明了结论的正确性与可行性.     

平均采样定理

采样定理是信号分析中的基本工具之一,广泛应用于数字信号处理、无线通信等很多领域.近年来,经典的Shannon采样定理被从频谱有限函数空间推广到更一般的平移不变子空间,采样方法也从逐点取值推广到平均采样和多通道采样等.本文简要回顾采样定理的发展过程,重点介绍一些最新研究进展,包括平均采样、多通道采样和随机过程采样等,以及混淆误差和截断误差等重构误差估计.     

一类不确定随机非线性系统的采样扩张状态观测器设计与观测误差的收敛性分析

实际系统中普遍存在各种干扰和不确定性因素,并且对控制系统的性能造成负面影响,因此设计对干扰和不确定性具有优异估计性能的观测器显得尤为重要.针对一类具有采样输出的不确定随机非线性系统,设计相应的采样扩张状态观测器用于在线估计不可量测状态和影响系统性能的随机总干扰.所估计的随机总干扰包含系统内部未建模动态、统计特性未知的外部有界噪声干扰以及不确定性因素的非线性耦合作用.在每个采样区间内,设计一个输出预估器用于估计实际输出,相应的输出估计值用于采样扩张状态观测器的设计.证明了所设计的采样扩张状态观测器对不可量测状态和随机总干扰的观测误差的均方收敛性.最后,一个具体仿真实例用于证实理论结果.     

内部输入带不同时滞的Timoshenko梁的指数稳定性

研究了内部输入带不同时滞的Timoshenko梁的指数稳定性.利用Smith预估器的思想,对部分状态进行预估可得无时滞系统.对无时滞系统设计控制器,得到闭环系统.通过讨论闭环系统的稳定性及原时滞系统和无时滞系统的误差系统的指数衰减,最终得出原系统的指数稳定性.     

分数阶双指数混沌系统的自适应滑模同步

研究了分数阶双指数混沌系统的自适应滑模同步问题.通过设计滑模函数和控制器,构造了平方Lyapunov函数进行稳定性分析.利用Barbalat引理证明了同步误差渐近趋于零,获得了系统取得自适应滑模同步的充分条件.数值仿真结果表明:选取适当的控制器及与滑模函数,分数阶双指数混沌系统取得自适应滑模同步.     

A method for solving a boundary problem for a nonlinear controlled system

An algorithm is proposed for constructing a control function that transfers a wide class of nonlinear systems of ordinary differential equations from an initial state to an arbitrarily small neighborhood of a given terminal state. The algorithm is convenient for numerical implementation. Taking into account the restrictions on the control and phase coordinates, a constructive criterion is obtained for choosing terminal states for which this transfer is possible. The problem of an interorbital flight is considered and modeled numerically.     

Approximate output tracking of a nonlinear system in the singular case

The paper considers the realization of a specified function on the output of a system linear in control. The control realizing the given function has singularities, which are an obstacle to the realization of the specified function on the entire time interval in the class of admissible controls. An approximation of the given function is constructed on the system output. A control is found such that the output is contained in an arbitrarily small neighborhood of the given function. The conditions for the existence of an approximation are obtained, and an algorithm to construct the approximating control is described.Translated from Nelineinye Dinamicheskie Sistemy: Kachestvennyi Analiz i Upravlenie Sbornik Trudov, No. 2, pp. 32–38, 1993.     

A novel adaptive non-backstepping VUFC algorithm for a class of MIMO nonlinear systems with unknown dead-zones in pure-feedback form

In this paper, based on adaptive non-backstepping design algorithm, we proposed a novel variable universe fuzzy control (VUFC) algorithm for a class of MIMO nonlinear systems with unknown dead-zone inputs in pure-feedback form. First, by introducing some new states variables and coordinate transforms, the system is converted form the state-feedback control of pure-feedback form into the output-feedback control of normal form. Secondly, different from traditional backstepping scheme,we introduce contraction–expansion factors, combine non-backstepping control technique and VUFC scheme together to construct the controllers and observers. VUFC approach is mainly based on changing the contraction–expansion factor to change the universe of the variables (which can change the interpolation node encryption). It is shown that the proposed control approach is considerably simpler and better than the backstepping-based ones and it can improve the accuracy of the system, alleviate tracking error, strong robustness. At last, according to stable positive real (SPR)-Lyapunov stability analysis, it can guarantee that all the signals in the closed-loop system are bounded and the output can tack the reference signal to a small neighborhood of the origin. Simulations results are illustrated that the effectiveness of the proposed VUFC approach.     

Adaptive fuzzy backstepping control design for a class of pure-feedback switched nonlinear systems

In this paper, an adaptive fuzzy output tracking control approach is proposed for a class of single input and single output (SISO) uncertain pure-feedback switched nonlinear systems under arbitrary switchings. Fuzzy logic systems are used to identify the unknown nonlinear system. Under the framework of the backstepping control design and fuzzy adaptive control, a new adaptive fuzzy output tracking control method is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error remains an adjustable neighborhood of the origin. A numerical example is provided to illustrate the effectiveness of the proposed approach.     

Adaptive fuzzy backstepping control for a class of MIMO switched nonlinear systems with unknown control directions

In this article, an adaptive fuzzy output tracking control approach is proposed for a class of multiple‐input and multiple‐output uncertain switched nonlinear systems with unknown control directions and under arbitrary switchings. In the control design, fuzzy logic systems are used to identify the unknown switched nonlinear systems. A Nussbaum gain function is introduced into the control design and the unknown control direction problem is solved. Under the framework of the backstepping control design, fuzzy adaptive control and common Lyapunov function stability theory, a new adaptive fuzzy output tracking control method is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed‐loop system are bounded and the tracking error remains an adjustable neighborhood of the origin. A numerical example is provided to illustrate the effectiveness of the proposed approach. © 2015 Wiley Periodicals, Inc. Complexity 21: 155–166, 2016     

A new second-order corrector interior-point algorithm for semidefinite programming

In this paper, we propose a second-order corrector interior-point algorithm for semidefinite programming (SDP). This algorithm is based on the wide neighborhood. The complexity bound is O(?nL){O(\sqrt{n}L)} for the Nesterov-Todd direction, which coincides with the best known complexity results for SDP. To our best knowledge, this is the first wide neighborhood second-order corrector algorithm with the same complexity as small neighborhood interior-point methods for SDP. Some numerical results are provided as well.     

A hybrid genetic local search algorithm for the permutation flowshop scheduling problem

Traditionally, the permutation flowshop scheduling problem (PFSP) was with the criterion of minimizing makespan. The permutation flowshop scheduling problem to minimize the total flowtime has attracted more attention from researchers in recent years. In this paper, a hybrid genetic local search algorithm is proposed to solve this problem with each of both criteria. The proposed algorithm hybridizes the genetic algorithm and a novel local search scheme that combines two local search methods: the Insertion Search (IS) and the Insertion Search with Cut-and-Repair (ISCR). It employs the genetic algorithm to do the global search and two local search methods to do the local search. Two local search methods play different roles in the search process. The Insertion Search is responsible for searching a small neighborhood while the Insertion Search with Cut-and-Repair is responsible for searching a large neighborhood. Furthermore, the orthogonal-array-based crossover operator is designed to enhance the GA’s capability of intensification. The experimental results show the advantage of combining the two local search methods. The performance of the proposed hybrid genetic algorithm is very competitive. For the PFSP with the total flowtime criterion, it improved 66 out of the 90 current best solutions reported in the literature in short-term search and it also improved all the 20 current best solutions reported in the literature in long-term search. For the PFSP with the makespan criterion, the proposed algorithm also outperforms the other three methods recently reported in the literature.     

A method for solving boundary value problems for nonlinear control systems in the class of discrete controls

We suggest an algorithm for constructing discrete control functions. This algorithm is sufficiently convenient for numerical implementation and, for a wide class of nonlinear systems of ordinary differential equations, provides the passage from the initial state into an arbitrary given or arbitrarily small neighborhood of a given terminal state. We obtain a constructive criterion for the choice of terminal states and discretization steps for which the passage is possible with regard of the constraints imposed on the control and the phase coordinates. We consider an interorbital flight problem, for which we carry out numerical simulation.     

半定规划的一个新的宽邻域非可行内点算法

基于一种新的宽邻域,提出一个求解半定规划的新的非可行内点算法．在适当的假设条件下,证明了该算法具有较好的迭代复杂界O（√nL）,优于目前此类算法的最好的复杂性O（n√nL）,等同于可行内点算法．     

卫星姿态跟踪的间接自适应模糊预测控制

对含模型不确定性和未知干扰的卫星姿态系统提出了具有间接自适应模糊补偿的广义预测跟踪控制方法. 首先基于卫星姿态动力学模型设计了非线性广义预测控制律, 再利用自适应模糊系统逼近预测控制律中的模型不确定项, 使得所得到的预测控制算法可实施.证明了当卫星姿态模型中不确定项满足一定条件时, 所设计的控制律可使卫星姿态跟踪误差收敛到原点的小邻域内,并仿真结果验证了所提出方法的有效性.