Finite Time Consensus Problem for Multiple Non-Holonomic Agents with Communication Delay

In this paper, finite time consensus problem is discussed for multiple non-holonomic mobile agents with constant communication delay. The objective is to design non-smooth distributed control laws such that multiple non-holonomic mobile agents can be all in agreement within any given finite time larger than communication delay. The authors propose a novel switching control strategy with the help of Lyapunov-based method and graph theory.     

基于GA-Fuzzy的混沌系统辨识研究

提出用遗传算法优化的Takagi-Sugeno-Kang(TSK)模糊模型对未知或不确定的混沌动力学系统进行辨识。在辨识未知混沌系统的TSK模型过程中，只需利用未知混沌系统的输出时间序列。首先，采用模糊聚类分析方法从训练数据建立其初始TSK模糊模型。然后采用实数编码的遗传算法对初始模型进行优化设计。同时为防止破坏模糊规则的语义属性，对遗传搜索空间采取了适当的限制。用辨识模型重建吸引子方法定性地评价辨识模型，通过计算辨识模型的Lyapunov指数定量地评价辨识模型的性能。仿真结果表明，该辨识模型能很好地逼近原混沌动力学系统，准确地体现原混沌系统的动力学特性。     

Generating semi-algebraic invariants for non-autonomous polynomial hybrid systems

Hybrid systems are dynamical systems with interacting discrete computation and continuous physical processes, which have become more common, more indispensable, and more complicated in our modern life. Particularly, many of them are safety-critical, and therefore are required to meet a critical safety standard. Invariant generation plays a central role in the verification and synthesis of hybrid systems. In the previous work, the fourth author and his coauthors gave a necessary and sufficient condition for a semi-algebraic set being an invariant of a polynomial autonomous dynamical system, which gave a confirmative answer to the open problem. In addition, based on which a complete algorithm for generating all semi-algebraic invariants of a given polynomial autonomous hybrid system with the given shape was proposed. This paper considers how to extend their work to non-autonomous dynamical and hybrid systems. Non-autonomous dynamical and hybrid systems are with inputs, which are very common in practice; in contrast, autonomous ones are without inputs. Furthermore, the authors present a sound and complete algorithm to verify semi-algebraic invariants for non-autonomous polynomial hybrid systems. Based on which, the authors propose a sound and complete algorithm to generate all invariants with a pre-defined template.     

An augmented BV setting for feedback switching control

<正> This paper considers dynamical systems under feedback with control actions limited toswitching.The authors wish to understand the closed-loop systems as approximating multi-scale problemsin which the implementation of switching merely acts on a fast scale.Such hybrid dynamicalsystems are extensively studied in the literature,but not much so far for feedback with partial stateobservation.This becomes in particular relevant when the dynamical systems are governed by partialdifferential equations.The authors introduce an augmented BV setting which permits recognition ofcertain fast scale effects and give a corresponding well-posedness result for observations with such minimalregularity.As an application for this setting,the authors show existence of solutions for systemsof semilinear hyperbolic equations under such feedback with pointwise observations.     

Logistic-Map混沌扩频序列的有限精度实现新方法

结合线性反馈移位寄存器 (linearfeedbackshiftregister,LFSR)最大长度码序列 ,提出一种收缩法来实现有限精度数字混沌系统。研究了扩频码的周期和相关性能与实现精度和LFSR的级数的关系 ,在较低精度和LFSR的级数不高的条件下能够产生统计性能逼近于理想随机序列的码族极大的混沌扩频序列     

New chaotic system and its hyperchaos generation

To seek for lower-dimensional chaotic systems that have complex topological attractor structure with simple algebraic system structure, a new chaotic system of three-dimensional autonomous ordinary differential equations is presented. The new system has simple algebraic structure, and can display a 2-scroll attractor with complex topological structure, which is different from the Lorenz’s, Chen’s and L¨u’s attractors. By introducing a linear state feedback controller, the system can be controlled to generate a hyperchaotic attractor. The novel chaotic attractor, hyperchaotic attractor and dynamical behaviors of corresponding systems are further investigated by employing Lyapunov exponent spectrum, bifurcation diagram, Poincar′e mapping and phase portrait, etc., and then verified by simulating an experimental circuit.     

基于神经网络的Lyapunov指数谱的计算

利用 BP神经网络的非线性函数逼近能力 ,由实验观察数据列计算系统的 Lyapunov指数谱 .实例计算表明 ,此种方法精度较高且计算量较小 ,有重要的实际意义.     

分数阶混沌系统的仿真方法研究

针对分数阶混沌系统的理论分析比较烦琐,基于分数阶混沌系统常用的频域和时域两种分析方法,研究了,分数阶混沌系统的动态仿真、电路仿其和数值仿真3种仿真方法。利用分数阶积分算子的频域描述函数,设计了分数阶积分算子的动态仿真模块和等效电路模块,通过分数阶混沌系统动态仿真和电路仿真,可实时地观察系统变量的演化规律;采用分数阶微分算子的Adams．Bashforth-Moulton预估校正算法,实现了分数盼琨沌系统的数值仿真,利用仿真输出数据可分析分数阶混沌系统的动力学特性。分数阶非耗散Lorenz混沌系统仿真实例证明了这3种仿真方法的有效性。     

Dynamical Criticality: Overview and Open Questions

Systems that exhibit complex behaviours are often found in a particular dynamical condition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in a dynamical regime between order and disorder attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, neuroscience and computer science have revitalised the interest in the criticality hypothesis, emphasising its role as a viable candidate general law in adaptive complex systems. This paper provides an overview of the works on dynamical criticality that are — To the best of our knowledge — Particularly relevant for the criticality hypothesis. The authors review the main contributions concerning dynamics and information processing at the edge of chaos, and illustrate the main achievements in the study of critical dynamics in biological systems.Finally, the authors discuss open questions and propose an agenda for future work.     

新分数阶混沌系统的异结构同步及其电路仿真

提出了一个新分数阶三维混沌系统,对其进行理论分析和数值仿真,仿真结果表明其存在混沌的最小阶数为2.34阶。基于主动控制法设计一个异结构同步控制器,电路仿真实现了该新分数阶混沌系统与分数阶lü系统的异结构同步。实验结果证明了该控制器的有效性和可行性。     

未知混沌系统同步自适应控制及其仿真研究

研究了参数未知情况下，混沌系统的同步自适应控制问题。利用滑模控制思想设计了动态神经网络。应用这种神经网络辨识系统，利用最优控制理论设计同步自适应控制器。最后针对Chua’s电路系统进行了数值仿真，结果证明本文所给方法的有效性。     

全局动力学模型用于水声信号分类仿真实验研究

水下弱信号的检测和分类是水声信号处理领域中的难题。本文研究了一种使用混沌动力学系统理论中全局动力学模型进行水声信号检测和分类的方法，用仿真数据对所建模型的有效性进行了验证。通过将模型拟合到几种舰船辐射噪声，成功地对其进行了分类。仿真结果表明，该方法在高噪声背景下（信噪比为OdB时）仍能对信号进行分类，且分类概率可以从模型系数空间的系统统计特性中直接计算得到。     

基于动态混沌神经网络的预测研究——以马铃薯时间序列价格为例

针对农产品价格波动的非线性特征明显、传统时间序列方法在预测农产品价格短期波动存在不足等状况,本文将混沌理论和神经网络技术应用到农产品价格短期预测研究中,充分利用相关技术优势,设计了动态混沌神经网络时间序列预测模型.在此基础上,选取2008年1月21日-2012年7月1日的中国马铃薯日度价格为研究对象,对所构建的动态混沌神经网络时间序列预测模型进行学习、训练和测试,并用统计分析方法对模型性能进行评价与分析,最后,将所构建模型的预测结果与传统预测方法预测出的结果进行比较研究.结果显示:整个动态混沌神经网络结构为27-12-1,所设计的基于动态混沌神经网络的马铃薯价格时间序列预测模型在预测精度和性能上较ARMA模型均具有明显优势,这一预测模型在农产品价格时间序列短期预测研究上将具有广阔的应用前景.     

Stability radius of non-smooth pritchard-salamon systems and the algebraic Riccati equation

The authors discuss the stability radius of the non-smooth Pritchard-Salamon systems under structured perturbations. A formula for the stability radius in terms of the norm of a certain input-output operator is obtained. Furthermore, the relationship between stability radius and the solvability of some type of algebraic Riccati equations is given. This research is supported by the National Natural Science Foundation of China under Grant Nos. 10626057 and 10571165.     

数组微分方程组广义同步系统理论研究

实现数组微分动力系统广义同步是进行图像保密通信的前提。在引入映射在矩阵域中下降这一新定义的基础上,提出了一个实现数组微分动力系统广义同步的新定理,给出了广义系统初始条件选取的方法,据此可构造通过线性变换达到广义同步的数组微分动力系统,即理论上可以构造出图像保密通信的发射系统和接收系统。通过引入实例,说明该定理构造一个广义同步的数组微分动力系统。数值模拟结果结果表明,运用定理构造成的数组广义同步系统实现了混沌广义同步。     

基于T-S模糊模型的临界混沌系统复杂动力学分析

针对新近提出的临界混沌系统,在其相应的Takagi-Sugeno(T-S)模糊模型基础上,通过给每个模糊规则后件施加一类扰动并调节这些扰动,深入研究了该混沌系统的复杂动力学特性.仿真结果表明:除了具有已经发现的由镜相形成机制所决定的复合结构外,该混沌系统仍然具有尚未发现的由压缩和拉伸形成机制所决定的其他复杂动力学行为.     

高阶非线性时滞系统的神经网络动态面控制

针对一类具有未知时变时滞的不确定高阶非线性系统,基于增加幂次积分方法,提出了一种非光滑状态反馈自适应神经网络动态面控制设计方案。通过构造适当的Lyapunov Krasovskii泛函处理了未知时变时滞不确定项;通过利用神经网络权值范数的适当形式幂次函数,将神经网络用于对在单步递推中所构造的未知函数进行建模;采用动态面技术,解决了“微分爆炸”问题。所提控制方案能够保证闭环控制系统的状态量和跟踪误差半全局一致终结有界。最后,仿真算例结果表明了该方案的有效性。     

Periodic performance of the chaotic spread spectrum sequence on finite precision

It is well known that the periodic performance of spread spectrum sequence heavily affects the correlative and secure characteristics of communication systems.The chaotic binary sequence is paid more and more attention since it is one kind of applicable spread spectrum sequences.However,there are unavoidable short cyclic problems for chaotic binary sequences in finite precision.The chaotic binary sequence generating methods are studied first.Then the short cyclic behavior of the chaotic sequences is analyzed in detail,which are generated by quantification approaches with finite word-length.At the same time,a chaotic similar function is defined for presenting the cyclic characteristics of the sequences.Based on these efforts,an improved method with scrambling control for generating chaotic binary sequences is proposed.To quantitatively describe the improvement of periodic performance of the sequences,an orthogonal estimator is also defined.Some simulating results are provided.From the theoretical deduction and the experimental results,it is concluded that the proposed method can effectively increase the period and raise the complexity of the chaotic sequences to some extent.     

Periodic performance of the chaotic spreadspectrum sequence on finite precision

It is well known that the periodic performance of spread spectrum sequence heavily affects the correlative and secure characteristics of communication systems. The chaotic binary sequence is paid more and more attention since it is one kind of applicable spread spectrum sequences. However, there are unavoidable short cyclic problems for chaotic binary sequences in finite precision. The chaotic binary sequence generating methods are studied first. Then the short cyclic behavior of the chaotic sequences is analyzed in detail, which are generated by quantification approaches with finite word-length. At the same time, a chaotic similar function is defined for presenting the cyclic characteristics of the sequences. Based on these efforts, an improved method with scrambling control for generating chaotic binary sequences is proposed. To quantitatively describe the improvement of periodic performance of the sequences, an orthogonal estimator is also defined. Some simulating results are provided. From the theoretical deduction and the experimental results, it is concluded that the proposed method can effectively increase the period and raise the complexity of the chaotic sequences to some extent.     

Finite-time neural funnel control for motor servo systems with unknown input constraint

In this paper, a finite-time neural funnel control (FTNFC) scheme is proposed for motor servo systems with unknown input constraint. To deal with the non-smooth input saturation constraint problem, a smooth non-affine function of the control input signal is employed to approximate the saturation constraint, which is further transformed into an affine form according to the mean-value theorem. A fast terminal sliding mode manifold is constructed by using a novel funnel error variable to force the tracking error falling into a prescribe boundary within a finite time. Then, a simple sigmoid neural network is utilized to approximate the unknown system nonlinearity including the saturation. Different from the prescribed performance control (PPC), the proposed finite-time neural funnel control avoids using the inverse transformed function in the controller design, and could guarantee the prescribed tracking performance without knowing the saturation bounds in prior. The effectiveness and superior performance of the proposed method are verified by comparative simulation results.