一类混沌神经网络的观测器广义投影同步设计

研究了混沌神经网络的广义投影同步问题.基于改进的非线性状态观测器理论和极点配置技术,设计了一种新的广义投影同步方案.该方案可以实现不同混沌神经网络之间的广义投影同步.通过对细胞神经元系统和三阶Winner-Take-All竞争型混沌神经元系统的数值仿真试验,进一步验证了所提方案的有效性.该方案具有全局性,与混沌神经网络的初始条件无关,且可以灵活地调整同步误差的收敛速度.     

控制混沌振动的局部逆系统算法

研究用局部逆系统方法控制混沌。将逆系统控制律局部线性化建立了局部逆系统控制律关分析了在控制混沌振动中的适用性,通过数值算例与逆系统方法进行了比较并讨论了控制方案的鲁棒性。     

混沌时序神经网络建模及其在保密通讯中的应用

本文在研究预报误差算法对混沌时序神经网络建模的应用和离散系统中基于压缩映射混沌同步的基础上，把混沌时序的错综复杂和于混沌同步保密通讯。     

离散神经网络中的分岔,混沌及控制混沌

本文通过数值方法研究了一类离散神经网络中“内依马克－沙克分岔”、混沌及控制混沌问题。在分岔出现后，随着参数的改变发现不变吉Γβ湮来现象。对一类混沌给出其活动区域的。研究了周期比例脉冲方法（ＧＭ方法）控制混沌在离散神经网络中的应用，讨论了其控制混沌的策略与机制，提出一种变幅值冲控制方法，比ＧＭ方法有明显优点。     

基于混沌神经网络理论的城市地面沉降量预测模型

通过分析城市地面沉降量时间序列的非线性动力学系统,认为该时间序列具有混沌特性。在此基础上,通过相空间重构的方法建立了用于城市地面沉降量预测的混沌神经网络模型;并利用此模型对高桥地面沉降量进行了预测,并和实际监测沉降量进行了比较,最大绝对预测误差为1. 7,预测的平均误差为0. 0833,研究结果表明,应用混沌神经网络模型进行城市沉降预测是可行、精确的。     

延时神经网络混沌现象的研究

本文研究一个具有部分延时性能的三个神经元的不对称神经网络系统的动力学行为，讨论了当控制参数变化时网络呈现的各种现象，计算了李雅普人指数研究了阵发混沌现象，最后讨论了全延时神经网络的吸引子。     

神经网络混沌运动的控制--CM方法

基于压缩映射的混沌控制方法——CM方法被应用到小的离散神经网络,通过一个外部输入的小干扰,稳定混沌轨道嵌入在混沌吸引子内的某一不稳周期轨上。利用闭回路对技术估计欲稳定周期轨的近似位置。给出二维和三维神经网络的典型例子,通过数值模拟显示CM方法控制离散神经网络混沌行为的简单和有效性。     

受迫Duffing振子中混沌运动的控制

本文研究了受迫Ｄｕｆｆｉｎｇ振子发生混沌运动时的控制问题，通过周期激振力、自适应控制和连续反馈控制来抑制、控制其中的混沌运动，使系统从混沌运动状态转变变到规则运动状态。     

混沌时间序列建模及预测

许多看似随机的时间序列可能是非线性确定系统的混沌行为所导致的结果。本文讨论了混沌时间序列的建模及预测方法,给出了各重要参数的选择取算法,并应用于实例,与传统的时间序列预测方法相比较,取得了精度更高的预测结果,从而为一类非线性时间序列提供了从数据采集识别到建模预测的完整技术。     

连续时间系统的混沌同步

本文讨论混沌连续时间系统的完全同步问题，提出一个构造混沌同步系统的新方法。这个方法基于线性系统的稳定性分析准则。通过对系统线性项与非线性项的适当分离，当系统的雅可比矩阵的所有特征值都具有负实部时，同步误差e(t)的线性系统是渐进稳定的，即可实现新系统和原系统的完全同步。新方法不需计算条件Lyapunov指数以作为判定同步的条件，因而比通用方法更为简单有效。新方法适用于自治或非自治系统，尤其适用于具有多于两个正Lyapunov指数的超混沌系统。甚至当初始同步误差极大时，也能实现理想的混沌同步。以Lorenz系统，耦合Duffing振子系统和超混沌Roessler系统作为算例。数值计算结果证实所提出方法的有效性和鲁棒性。     

Fuzzy-approximation-based adaptive control of the chaotic permanent magnet synchronous motor

This paper focus on the problem of position tracking control for the chaotic permanent magnet synchronous motor drive system with parameter uncertainties. Fuzzy logic systems are used to approximate the nonlinearities and the adaptive backstepping technique is employed to construct controllers. The proposed adaptive fuzzy controllers guarantee that the tracking error converges to a small neighborhood of the origin. Compared with the conventional backstepping, the designed fuzzy controllers?? structure is very simple. Simulation results show that the proposed control scheme can suppress chaos of PMSM and guarantee the perfect tracking performance even under the unknown parameters.     

A robust-adaptive fuzzy coverage control for robotic swarms

In this paper, a decentralized adaptive control scheme for multi-robot coverage is proposed. This control method is designed based on centroidal Voronoi configuration integrated with robust adaptive fuzzy control techniques. We consider simple single integrator mobile robots used for covering dynamical environments, where an adaptive fuzzy logic system is used to approximate the unknown parts of control law. A robust coverage criterion is used to attenuate the adaptive fuzzy approximation error and measurement noises to a prescribed level. Therefore, the robots motion is forced to obey solutions of a coverage optimization problem. The advantages of the proposed controller can be listed as robustness to external disturbances, computation uncertainties, and measurement noises, while applicability on dynamical environments. A Lyapunov-function based proof is given of robust stability, i.e. convergence to the optimal positions with bounded error. Finally, simulation results are demonstrated for a swarm coverage problem simultaneous with tracking mobile intruders.     

Synchronization of two different chaotic systems using novel adaptive interval type-2 fuzzy sliding mode control

In this paper, we use sliding mode control integrated with an interval type-2 fuzzy system for synchronization of two different chaotic systems in presence of system unmodeling and external disturbances. To reduce the chattering and improve the robustness of reaching phase of the Sliding Mode Control (SMC), an interval fuzzy type-2 logic controller is used. In addition, an adaptive interval type-2 fuzzy inference approximator is proposed (as equivalent control part of SMC) to approximate the unknown parts of the uncertain chaotic system. Using type-2 fuzzy systems makes more effective synchronization results in presence of system uncertainty and disturbances in comparison with type-1 fuzzy approximators. The stability analysis for the proposed control scheme is provided, and simulation results compare the performance of interval type-2 fuzzy and type-1 fuzzy controllers to verify the effectiveness of the proposed method.     

非线性振动一种稳定的模糊控制方法研究

由于非线性振动系统的非线性本质,在于传统控制理论的线性控制器用于非线性振动控制效果不佳。本文针对非线性振动系统提出了一种模糊自适应滑模控制方案。     

Fuzzy adaptive high-gain-based observer backstepping control for SISO nonlinear systems with dynamical uncertainties

In this paper, a fuzzy adaptive output feedback control approach is developed for a class of SISO strict-feedback nonlinear systems with unmeasured states, unmodeled dynamics, and dynamical disturbances. In the backstepping recursive design, fuzzy logic systems are used to approximate the unknown nonlinear functions, a fuzzy adaptive high-gain observer is designed to estimate the unmeasured states; a dynamic signal is incorporated into the control scheme to dominate the dynamic uncertainties. Using the states estimates and combining the backstepping design technique, a fuzzy adaptive output feedback control is constructed recursively. It is proved that the proposed fuzzy adaptive output feedback control scheme can guarantee the all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SUUB), and the observer and tracking error converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated via an example.     

Adaptive dynamic surface control for MEMS triaxial gyroscope with nonlinear inputs

An adaptive dynamic surface control algorithm that incorporates adaptive control and fuzzy logic system into the implementation of dynamic surface control for regulating problem of MEMS triaxial gyroscope subject to external disturbance, uncertainty and input uncertainty is developed in this work. To relax the requirement of exact model and obtain fully adaptive property, a fuzzy logic system is introduced to approximate the uncertainty. With adaptive control structure, the proposed controller can obtain the properties of fast dynamic response and high tracking-accuracy, even the existence of disturbance, uncertainty and control input nonlinearity. All parameters adjustment rules for the proposed control scheme are derived from Lyapunov theory such that the trajectory of tracking-error converges to the small neighborhood of equilibrium point. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.     

Adaptive fuzzy backstepping output feedback control of nonlinear uncertain time-delay systems based on high-gain filters

In this paper, an adaptive fuzzy output feedback control approach is developed for a class of SISO uncertain nonlinear strict-feedback systems. The considered nonlinear systems contain unknown nonlinear functions, unknown time-varying delays and unmeasured states. The fuzzy logic systems are first used to approximate the unknown nonlinear functions, and then a high-gain filter is designed to estimate the unmeasured states. Combining the backstepping recursive design technique and adaptive fuzzy control design, an adaptive fuzzy output feedback backstepping control method is developed. It is proved that the proposed adaptive fuzzy control approach can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and both the observer error and tracking error converge to a small neighborhood of the origin. Two key advantages of our scheme are that (i) the high-gain filter is designed to estimate unmeasured states of time-delay nonlinear system, and (ii) the virtual control gains are functions. A simulation is included to illustrate the effectiveness of the proposed approach.     

Fuzzy adaptive dynamic surface control for a single-link flexible-joint robot

In this paper, a fuzzy adaptive controller is proposed for a single-link flexible-joint robot. Fuzzy logic systems are used to approximate unknown nonlinearities, and then a fuzzy state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping design with dynamic surface control (DSC) technique, a fuzzy adaptive output-feedback backstepping control approach is developed. It is proved that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and both the observer and tracking errors converge to a small neighborhood of the origin by appropriate choosing the design parameters. The simulation results are provided to demonstrate the effectiveness of the proposed controller. Two key advantages of our scheme are that (i)?the proposed control method does not require that the link velocity and actuator velocity of single-link flexible-joint robot be measured directly, and (ii)?the problem of ??explosion of complexity?? is avoided.     

结构可靠度分析FORM迭代算法的混沌控制

利用混沌控制原理对FORM收敛失败进行控制. 理清了全局性和局部性两类混沌反馈 控制各种方法的内在联系,说明稳定转换法和自适应调节法属于全局混沌反馈控制 方法,自适应调节法可视为稳定转换法的特例. 参 数调节混合法不过是松弛牛顿法的另一种表达形式,它们都属于局部混沌反馈控制方法. 阐 明了混沌反馈控制表达式与工程力学收敛控制迭代算法的对应关系. 也揭示了这些迭代算法 收敛控制措施的功效和局限性. 提出了一个以稳定转换法为主联合松弛牛顿法的混 沌反馈控制方法,对可靠度分析FORM迭代算法实现了周期振荡、分岔和混沌控制.     

Prescribed performance adaptive fuzzy output-feedback control of uncertain nonlinear systems with unmodeled dynamics

In this paper, an adaptive fuzzy output-feedback control approach is proposed for a class of uncertain nonlinear systems with unknown nonlinear functions, unmodeled dynamics, and without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. To solve the problem of unmodeled dynamics, the dynamical signal combined with changing supply function is incorporated into the backstepping recursive design technique. Under the framework of the backstepping control design technique and incorporated by the predefined performance technique, a new robust adaptive fuzzy output feedback control scheme is constructed. It is shown that all the signals of the resulting closed-loop system are bounded, and the system output remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example and comparison with the previous control methods are provided to show the effectiveness of the proposed control approach.