一类振荡电路的混沌及其控制

研究了一个振荡电路的混沌形成过程,并利用分岔图、Lyapunov指数图以及相图分析了该系统的混沌行为.利用分岔控制和x|x|控制等两种方法实现了系统的混沌控制,将系统的混沌行为有效地控制到稳热定的周期轨道.其中,在分岔控制方法下,对受控系统做出了控制参数的系统分岔图,由分岔图可以得到控制到np的周期轨道的取值范围,在这范围内适当选择数值,将电路系统控制到p-1,p-2,p-4,p-8等周期轨道.x|x|控制是对混沌动力系统增加一个具有分段二次函数x|x|形式的非线性反馈控制器.仿真结果表明,这两种方法对控制电路系统的可行性.     

基于T-S模糊模型的Kawakami混沌系统的控制

研究了离散Kawakami混沌系统的模糊控制问题,利用单点模糊化、乘积推理和中心平均去模糊化模糊推理方法将Kawakami系统化为T-S模糊模型.在用T-S模糊模型重构了系统结构的基础上,利用反馈控制思想,借助于离散李亚普诺夫稳定性理论,给出了离散T-S模糊模型渐近稳定的充分条件,并设计出了相应的状态反馈控制器.利用线性矩阵不等式,进一步求出了模糊控制器的参数.仿真结果验证了该控制方法的有效性.     

基于自适应动态面的航向跟踪控制器设计

针对船舶航向控制非线性系统模型中存在的不确定性和外界干扰的影响,采用动态面控制算法设计了一种鲁棒自适应控制器。由于在反步法设计过程中加入了一阶低通滤波器使得该方法无需对模型非线性多次微分,因而设计方法简单。所设计的鲁棒自适应控制器不仅能保证闭环系统的半全局渐近稳定,使得输出渐进跟踪期望轨迹;而且,跟踪误差可以通过控制器的设计参数加以调整。以中远集装箱船COSCO Shanghai号为例进行仿真研究,结果证明所设计的控制器是有效的。     

船舶航向非线性系统的动态面控制

针对船舶航向控制非线性系统模型中存在的不确定性和外界干扰的影响,采用动态面控制算法设计了一种航向控制器。由于在反步法设计过程中加入了一阶低通滤波器使得该方法无需对模型非线性多次微分,因而设计方法简单,所设计的控制器能够保证闭环系统的半全局渐近稳定,使得输出渐进跟踪期望轨迹。数字仿真结果表明,控制系统对给定航向的跟踪具有良好的动态特性,对系统的不确定性,具有较强的鲁棒性。     

利用延迟反馈方法控制调速器系统的混沌

通过对机械式离心调速器系统增加一个延迟反馈控制器,利用它控制系统从混沌运动转化为周期运动.当该控制器的延迟时间等于系统的某一条不稳定轨道的周期时,就能将处于混沌状态的系统控制到相应的不稳定周期轨道上,并将该轨道稳定化.数值仿真表明了该控制方法在机械式离心调速器系统混沌控制中的有效性与可行性,将系统的混沌行为利用适当的控制强度控制到稳定的周期轨道.     

基于自适应非奇异终端滑模的悬浮控制策略

针对采用传统线性滑模控制的电磁悬浮系统存在响应速度慢以及抗干扰能力差的问题，提出了一种基于自适应非奇异终端滑模的悬浮控制方法，该方法将自适应控制引入到终端滑模控制，结合滑模控制对扰动不敏感的优点，利用自适应控制对滑模趋近律系数进行在线自适应调节，改善悬浮系统的动态性能. 首先，建立了电磁悬浮系统数学模型；然后，利用李雅普诺夫稳定理论证明了所设计控制器的稳定性；最后，进行了仿真和实验验证. 实验结果表明:自适应非奇异终端滑模对信号跟踪具有更快的响应速度和更小的稳态误差，对峰峰值为2 N的正弦或锯齿干扰力气隙波动可限定在0.2 mm以内，进行0.1 kg加减载实验时气隙波动为0.6 mm，各项性能均优于终端滑模和线性滑模.      

车辆多目标自适应巡航显式模型预测控制

为了兼顾车辆自适应巡航控制(ACC)系统的跟踪控制效果和实时性, 提出了基于显式模型预测控制(EMPC)理论的车辆多目标自适应巡航控制方法; 基于车辆间运动学关系建立自适应巡航控制运动学模型, 根据预测控制理论推导预测时域内的跟踪误差预测模型, 并确定车辆安全性、跟踪性、经济性和舒适性等多性能目标函数和约束条件; 运用显式模型预测控制中的多参数规划理论, 将基于反复在线优化计算的闭环模型预测控制系统转化为与之等价的显式多面体分段仿射(PPWA)系统, 通过离线计算获得期望加速度与距离误差、速度误差、自车加速度和前车加速度等状态变量之间的最优控制律, 并设计在线查表的搜索流程, 通过定位当前状态所处分区, 并应用该分区的显式控制律实现自适应巡航控制; 进行了纵向跟踪工况仿真验证, 并与传统MPC-ACC控制方法进行对比。对比结果表明: 在前车正弦加减速工况下, EMPC-ACC控制器单步运算速度比MPC-ACC控制器平均提升了53.51%, EMPC-ACC控制下的平均距离跟踪误差为0.220 3 m, 平均速度误差为0.340 1 m·s-1; 在前车阶跃加减速工况下, EMPC-ACC控制器单步运算速度比MPC-ACC控制器平均提升了72.96%, EMPC-ACC控制下的平均距离跟踪误差为0.331 9 m, 平均速度误差为0.399 1 m·s-1。可见, 提出的EMPC-ACC控制算法在保证纵向跟踪性能的前提下, 有效地提高了自适应巡航控制的实时性。      

Hierarchical control strategy of trajectory tracking for intelligent vehicle

In order to track the desired trajectory for intelligent vehicle, a new hierarchical control strategy is presented. The control structure consists of two layers. The high-level controller adopts the model predictive control (MPC) to calculate the steering angle tracking the desired yaw angle and the lateral position. The low-level controller is designed as a gain-scheduling controller based on linear matrix inequalities. The desired longitudinal velocity and the yaw rate are tracked by the adjustment of each wheel torque. The simulation results via the high-fidelity vehicle dynamics simulation software veDYNA show that the proposed strategy has a good tracking performance and can guarantee the yaw stability of intelligent vehicle.     

Hierarchy-Based Adaptive Generalized Predictive Control for Aerial Grasping of a Quadrotor Manipulator

In this paper, an adaptive generalized predictive control(GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structure is adopted to achieve more precise trajectory tracking and keep the tracking performance after aerial grasping.The inner-layer controller is a proportional-derivative(PD) controller. The outer-layer subsystem is linearized by input-output linearization first and an adaptive generalized predictive controller is applied. The effectiveness of this approach is verified through the simulation using MATLAB/Simulink. A PD controller with feedforward control input is applied on such a system for a comparative study. Simulation results show that a better tracking performance can be achieved by the proposed strategy.     

MODELING OF NONLINEAR SYSTEMS BY MULTIPLE LINEARIZED MODELS

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Nonlinear control for autonomous underwater glider motion based on inverse system method

Autonomous underwater gliders are highly efficient, buoyancy-driven, winged autonomous underwater vehicles. Their dynamics are multivariable nonlinear systems. In addition, the gliders are underactuated and difficult to maneuver, and also dependent on their operational environment. To confront these problems and to design an effective controller, the inverse system method was used to decouple the original system into two independent single variable linear subsystems. The stability of the zero dynamics was analyzed, and an additional closed-loop controller for each linear subsystem was designed by sliding mode control method to form a type of composite controller. Simulation results demonstrate that the derived nonlinear controller is able to cope with the aforementioned problems simultaneously and satisfactorily.     

基于模型预测控制的智能车横纵向控制器设计

针对智能车横纵向控制中路径跟踪精度、行驶稳定性以及乘坐舒适性等问题,提出了基于模型预测控制(MPC)的横纵向综合控制方法。速度规则系统根据参考路径曲率与车辆跟踪位移误差计算出期望速度曲线,速度跟踪控制采用分层式控制器,上层控制器利用MPC算法计算期望加速度,下层控制器利用车辆逆纵向动力学模型对车辆的驱动和制动进行协调控制。横向控制器根据参考路径、车辆反馈状态以及纵向上层控制器的期望速度计算车辆前轮转角。最后通过实验对比本算法与恒速MPC横向控制算法的轨迹误差,结果表明:本算法控制的车辆横向位移均方根误差减小了0.051 m,有效提高了车辆轨迹跟踪的控制精度。     

一类周期系数力学系统分岔控制

为了控制周期系数微分系统平衡点失稳后的分岔行为,基于Floquet-Lyapunov理论,将控制常系数系统分岔行为的方法（线性法、参数法、平移法）应用于一类具有周期系数的力学微分系统,设计了相应的控制器,研究了其控制平衡点分岔行为的有效性.研究结果表明:平移法不能有效控制周期系数微分系统的平衡点失稳后发生的Flip分岔和Hopf分岔行为.若平衡点失稳发生Flip分岔形成周期2点,可分别采用线性法和参数法将周期2点控制到周期1点;若平衡点失稳发生Hopf分岔形成Hopf圈,可分别采用线性法和参数法将Hopf圈控制到周期1点.      

Nonlinear pitch control of an underwater glider based on adaptive backstepping approach

Underwater gliders are highly efficient and long-ranged autonomous underwater vehicles. The typical dynamic modeling in the vertical plane is of multi-input multi-output(MIMO), which is underactuated while easily affected by the ambient environment. To resolve the problems of MIMO, the dynamic model is transformed into a single-input single-output(SISO) system with two dubious parameters, and an adaptive backstepping controller is designed and applied in this paper. A Lyapunov function has been established with the total energy of the system converged in the controller. Contrast result of simulation has demonstrated that the derived nonlinear controller has higher tracking precision and faster response than the proportional-integral-derivative(PID) control method,which indicates its excellent capability to deal with the controlling problems of underwater gliders.     

含有平方项的新混沌系统的研究及控制

在Lorenz系统及Liu系统的基础上,提出了一个新的三维连续自治系统,简述了该系统的基本动力学特征,根据Routh-Hurwitz准则,重点讨论了系统平衡点的稳定性.采用线性状态反馈控制证明了达到预期控制目标反馈控制参数的选取范围,数值仿真证明了该方法的有效性.     

Singular perturbation composite control of a free-floating flexible dual-arm space robot

The Free-floating Flexible Dual-arm Space Robot is a highly nonlinear and coupled dynamics system. In this paper, the dynamic model is derived of a Free-floating Flexible Dual-arm Space Robot holding a rigid payload. Furthermore, according to the singular perturbation method, the system is separated into a slow subsystem representing rigid body motion of the robot and a fast subsystem representing the flexible link dynamics. For the slow subsystem, based on the second method of Lyapunov, using simple quantitative bounds on the model uncertainties, a robust tracking controller design is used during the trajectory tracking phase. The optimal control method is designed in the fast subsystem to guarantee the exponential stability. With the combination of the two above, the system can track the expected trajectory accurately, even though with uncertainty in model parameters, and its flexible vibration gets suppressed, too. Finally, some simulation tests have been conducted to verify the effectiveness of the proposed methods.     

基于误差交叉耦合的多电磁铁悬浮系统滑模协同控制

针对磁浮列车传统的单点悬浮控制方法没有考虑多电磁铁间的协调同步问题,将多电磁铁的跟踪误差交叉耦合来设计高精度的协同控制方法,在减少了多点悬浮系统的跟踪误差和同步误差的同时,提高了系统抗干扰能力. 首先,通过动力学分析了考虑未知扰动的4个电磁铁（2个控制模块）悬浮系统的动力学特征;其次,针对系统中的未知扰动,引入干扰观测器来估计扰动并进行扰动补偿;然后,考虑到相邻电磁铁控制模块之间存在耦合动力学特性,设计一种误差交叉耦合的滑模协同控制器;最后,在不作任何线性化处理的前提下,证明了闭环系统的渐近稳定性. 研究结果表明:通过多电磁铁的悬浮架实验证明所提方法可以考虑补偿电磁铁模块之间的协调关系,抑制扰动的影响,减小间隙跟踪误差达40%,显著减少了电磁铁之间的耦合扰动作用.      

Peak current control strategy with extended-state tracking compensator for DC-DC in hybrid energy storage system

Because variations of ultra-capacitor voltage and battery voltage generate subharmonic and chaotic behaviors in hybrid energy storage system (HESS) application when a DC-DC converter is under the peak current control, a novel digital control strategy, i.e., peak current control with extended-state tracking compensator, is introduced to deal with the stability. The gains of the control algorithm are selected based on pole locations formulated from the Bessel filter. The simulation results validate that under the peak current control strategy with compensator, the DC-DC converter does not have the subharmonic and chaotic behaviors. The response time under the peak current control with compensator is the same as that under the peak current control. The ripple voltage and ripple current of battery are less. The tracking error of inductor current tends to zero.     

Inverse Learning Control of Nonlinear Systems Using Support Vector Machines

An inverse learning control scheme using the support vector machine (SVM) for regression was proposed. The inverse learning approach is originally researched in the neural networks. Compared with neural networks, SVMs overcome the problems of local minimum and curse of dimensionality. Additionally, the good generalization performance of SVMs increases the robustness of control system. The method of designing SVM inverse learning controller was presented. The proposed method is demonstrated on tracking problems and the performance is satisfactory.     

基于LS—SVM逆系统方法的非线性动态矩阵控制

针对神经网络逆系统建模存在的诸多问题,提出了基于最小二乘法支持向量机的α阶逆系统方法的非线性动态矩阵控制新方法．将最小二乘支持向量机辨识非线性对象的α阶逆模型与原系统串联组成伪线性系统,根据线性动态矩阵预测控制方法对伪线性系统进行控制．仿真结果表明,系统存在扰动和模型参数发生变化时,依然具有很好的动、静态性能,且表现出很强的鲁棒性,证明了方法的有效性．该方法不依赖于系统的数学模型,简化了非线性对象动态矩阵控制器的设计,为非线性预测控制的研究提供了一种新途径．