智能空间刚架的模糊自抗扰振动抑制研究

智能空间刚架作为太空望远镜支撑架是一种新型智能空间结构.为抑制刚架系统在运动过程中产生的振动,"文章提出了一种基于自抗扰控制的非线性模糊自抗扰控制理论,并设计出模糊自抗扰控制器.首先采用有限元方法计算出空间刚架的质量矩阵、阻尼矩阵和刚度矩阵,进而建立系统模型并设计出自抗扰控制器以实现对系统振动的抑制.基于普通自抗扰控制器,利用模糊推理在线整定控制器中非线性状态误差反馈的参数.该控制器不依赖于被控对象的精确数学模型,具有良好的控制性能,同时参数的在线自整定简化了调参难度.仿真实验验证了所提方法的有效性.     

不确定对象的自学习模糊神经网络控制方法

本文对具有不确定性控制对象提出了一种自学习模糊神经网络控制方法，模糊控制器采用误差，误差变化及误差加速度的加权和解析描述形式，利用人工神经网络直接对过程的建模，实现对模糊加权因子的自学习优化调整。将上述方法用于焊接熔池动态过程控制实实验，结果表明本文提出的自学习模糊神经网络控制方案有效。     

基于模糊自抗扰的塔机消摆控制方法

塔机消摆控制系统是一个非线性、强耦合的复杂系统,传统PID控制效果往往欠佳.对此,建立了一个含阻尼的塔机偏摆系统数学模型,并提出模糊自抗扰控制策略.通过自抗扰控制器对塔机回转与变幅运动进行解耦,模糊算法对自抗扰控制器各参数实施在线调整,并对解耦后的回转、变幅子系统分别进行控制.在仿真实验中,对比其他典型方法,提出的方法摆角消失速度更快,这表明在负载运动过程中,所设计控制器实时性和鲁棒性较好.     

基于GA-BP的模糊神经网络控制器与Elman辨识器的系统设计

提出了一种基于神经网络的模糊控制系统 ,该系统由模糊神经网络控制器和模型辨识网络组成 .文中介绍了模糊神经网络控制器采用遗传算法离线优化与 BP算法在线调整 ,给出了具体控制算法 ,推导了变形 Elmam网络的系统辨识算法 .仿真结果表明了此法的可行性和有效性 .     

基于准ARX多层学习网络模型的非线性系统自适应控制

建立了准ARX多层学习网络预测模型,并用于非线性系统自适应控制问题.该模型的内核部分为一个改进的神经模糊网络(NFNs):一部分为三层非线性网络结构,采用自联想网络进行离线训练;另一部分为三层NFNs,采取在线调整.据此对参数进行分类,给出相应调整算法. 然后,基于模型宏观结构的优势给出控制器设计方案.仿真分析给出该建模方法的有效性.     

基于区间2型T-S模糊系统的自适应逆控制

复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。     

Fuzzy关系方程干解在模糊在线控制系统中的应用研究

讨论了怎样快速求出Fuzzy关系方程干解的方法.探讨了该方法在模糊在线控制系统中的应用,同时给出了如何快速构建经济适用的动态模糊控制器的设计方法.     

一类具有泛逼近能力的模糊控制器的设计与等效分类

给出一些由模糊蕴涵算子构造的且具有泛逼近能力的模糊控制器。在等效的意义下,它们又可归结为30种,这些模糊控制器可以用于实际的模糊控制系统之中。     

非线性时滞系统自适应模糊动态面控制

针对未知非线性系统控制器设计过程中引入逼近器过多的问题,提出一种简化的自适应模糊动态面控制器设计方案.在控制器设计过程中,仅采用一个模糊逻辑系统作为逼近器,使得所有的未知项得到补偿,同时采用自适应技术在线辨识未知参数和逼近误差上界.文中的控制方案克服了传统backstepping控制器中"复杂性膨胀"的问题.通过构造合适的Lyapunov函数,证明闭环系统的所有信号为半全局最终一致有界.仿真实例验证所提出的控制方案的有效性.     

基于改进单神经元PID控制的主动悬架系统研究

汽车悬架是车身与车轮之间的传力连接装置。运用MATLAB/Simulink建立仿真模型,应用模糊理论在线调整比例系数改进单神经元PID控制并设计控制器,进行三种工况下的仿真验证。结果表明:控制策略可行且控制器有较强的鲁棒性,进一步改善了汽车行驶的平顺性。     

ON/OFF strategy based minimum-time control of continuous Petri nets

This paper focuses on the target marking control problem of timed continuous Petri nets (TCPN), aiming to drive the system from an initial state to a desired final one. This problem is similar to the set-point control problem in a general continuous-state system. In a previous work, a simple and efficient ON/OFF controller was proposed for Choice-Free nets, and it was proved to be minimum-time (Wang, 2010). However, for general TCPN the ON/OFF controller may bring the system to “blocking” situations due to its “greedy” firing strategy, and the convergence to the final state is not ensured. In this work the ON/OFF controller is extended to general TCPN by adding more “fair” strategies to solve conflicts in the system: the ON/OFF+ controller is obtained by forcing proportional firings of conflicting transitions. Nevertheless, such kind of controller might highly slow down the system when transitions have flows of different orders of magnitude, therefore a balancing process is introduced, leading to the B-ON/OFF controller. A third approach introduced here is the MPC-ON/OFF controller, a combination of Model Predictive Control (MPC) and the ON/OFF strategy; it may achieve a smaller number of time steps for reaching the final states, but usually requires more CPU time for computing the control laws. All the proposed extensions are heuristic methods for the minimum-time control and their convergences are proved. Finally, an application example of a manufacturing cell is considered to illustrate the methods. It is shown that by using the proposed controllers, reasonable numbers of time steps for reaching the final state can be obtained with low computational complexity.     

基于转换控制定律的倒立摆控制器设计(英文)

本文研究倒立摆的控制器设计.运用控制转换定律和Lyapunov第二方法,有效解决了由钟的分离角和控制系统中小车的置换引起的强非线性和强耦合性难题.并证明该控制器对由摆的长度和质量以及小车的质量等参数决定的非线性摩擦系数的变化具有强鲁棒性.最后,仿真实验结果证明了该控制器设计的可行性.     

A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems

An observer-based adaptive controller developed from a hierarchical fuzzy-neural network (HFNN) is employed to solve the controller time-delay problem for a class of multi-input multi-output (MIMO) non-affine nonlinear systems under the constraint that only system outputs are available for measurement. By using the implicit function theorem and Taylor series expansion, the observer-based control law and the weight update law of the HFNN adaptive controller are derived. According to the design of the HFNN hierarchical fuzzy-neural network, the observer-based adaptive controller can alleviate the online computation burden. Moreover, the common adaptive controller is utilized to control all the MIMO subsystems. Hence, the number of adjusted parameters of the HFNN can be further reduced. In this paper, we prove that the proposed observer-based adaptive controller can guarantee that all signals involved are bounded and that the outputs of the closed-loop system track asymptotically the desired output trajectories.     

一类具有饱和因子的奇异时滞系统的鲁棒保性能控制

研究了具有饱和因子的非线性奇异时滞系统的鲁棒保性能控制问题.目的是设计一个鲁棒控制器和保成本控制器,通过线性矩阵不等式方法(LMI)得出了鲁棒控制器和保性能控制器存在的充分条件.当这些LMI方法是可解时,分别给出了鲁棒控制器和保性能控制器的解析表达式.     

一类广义模糊控制系统及其特征

在具有再生核的希尔伯特空间中(简记为r．k.h，以下同)，以一组修正化的再生核作为输入空间的隶属函数，建立了一种广义的模糊控制系统，在一定条件下，该系统事实上包含着是r．k.h中函数的最佳插值逼近．就对未知控制曲线的逼近而言，典型的模糊控制器^[1]不可能比这种广义的模糊控制系统做得更好．广义的模糊系统具有以下优点：对样本的学习一次完成，克服了一般模糊控制器学习时所面临的解一个非线性最优化问题的困难；能估计出对待逼近实际控制函数误差的一个确定的上界；从Kosko B所揭示的模糊逼近本质特征^[2]，即确定性的角度来看它也是最优的．     

Time-Varying Linear-Quadratic Control

This paper discusses the performance of controlled linear dynamic systems that use time-varying feedforward signals and time-varying linear-quadratic (LQ) feedback gains. Such a time-varying LQ controller can bring a dynamic system to a desired final state in roughly half the time required by a time-invariant LQ controller, since it pushes at both ends, i.e., it uses significant control effort near the end of the maneuver, as well as at the beginning, to meet the specified end conditions; there is no overshoot and no settling time. This requires a more complex controller and some care with the high gains near the final time. A MATLAB³ code is listed that synthesizes and simulates zero-order-hold time-varying LQ controllers. The precision landing of a helicopter using four controls is treated as an example.     

Composite nonlinear feedback based discrete integral sliding mode controller for uncertain systems

In this paper, a discrete integral sliding mode (ISM) controller based on composite nonlinear feedback (CNF) method is proposed. The aim of the controller is to improve the transient performance of uncertain systems. The CNF based discrete ISM controller consists of a linear and a nonlinear term. The linear control law is used to decrease the damping ratio of the closed-loop system for yielding a quick transient response. The nonlinear feedback control law is used to increase the damping ratio with an aim to reduce the overshoot of the closed-loop system as it approaches the desired reference position. It is observed that the discrete CNF-ISM controller produces superior transient performance as compared to the discrete ISM controller. The closed-loop control system remains stable during the sliding condition. Simulation results demonstrate the effectiveness of the proposed controller.     

混沌记忆系统的自适应反馈控制和轨迹跟踪控制

研究了混沌记忆系统的自适应反馈控制和基于反馈线性化的轨迹跟踪控制问题.首先,通过绘制系统的时域波形图和混沌吸引子图验证系统的复杂的动力学行为;然后,分别应用自适应反馈控制方法和基于反馈线性化的轨迹跟踪控制方法设计控制器,对系统施加控制;最后,通过数值仿真验证控制器的有效性.     

Non zero-sum stochastic games in admission,service and routing control in queueing systems

The purpose of this paper is to investigate situations of non-cooperative dynamic control of queueing systems by two agents, having different objectives. The main part of the paper is devoted to analyzing a problem of an admission and a service (vacation) control. The admission controller has to decide whether to allow arrivals to occur. Once the queue empties, the server goes on vacation, and controls the vacations duration (according to the state and past history of the queue). The immediate costs for each controller are increasing in the number of customers, but no convexity assumptions are made. The controllers are shown to have a stationary equilibrium policy pair, for which each controller uses a stationary threshold type policy with randomization in at most one state. We then investigate a problem of a non-zero sum stochastic game between a router into several queues, and a second controller that allocates some extra service capacity to one of the queues. We establish the equilibrium of a policy pair for which the router uses the intuitive Join the shortest queue policy.     

多工作点加速度计组合件高精度鲁棒温度控制

将存在多个工作环境的加速度计组合件温度控制受控对象描述为存在有界时变参数摄动和有界干扰的非线性时变不确定系统,提出了一种基于信号补偿的鲁棒温度控制方法,该方法设计的控制器由标称控制器和鲁棒补偿器组成.证明了闭环系统的鲁棒控制特性,实验结果显示所设计的控制系统能够在多个工作环境下实现高精度的鲁棒温度控制.