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H∞环路成形方法设计的控制器阶次较高,不便于工程实现和参数调整;用传统方法确定模糊控制器隶属度函数的参数和模糊规则比较费时且难以保证鲁棒性能和时频域性能指标.针对上述情况,提出了一种综合运用H∞环路成形和自适应神经模糊推理系统来设计模糊控制器的方法.首先采用H∞环路成形设计方法,得到鲁棒裕量、动态和稳态性能都符合要求的控制器,然后用自适应神经模糊推理系统来逼近此控制器,最后根据自适应神经模糊推理系统参数确定相应的模糊控制器规则和参数.该方法确定模糊控制器隶属度函数的参数精确而省时,且能保证控制器具有较强的鲁棒性和良好的控制效果.通过对小车倒立摆系统进行的仿真,验证了该控制器设计方法的有效性. 相似文献
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本文提出了一种带有约束机构的并联柔索驱动转台,介绍该转台的机构构型,设计了一种利用模糊逻辑进行在线参数自适应的Fuzzy-PID控制器.该控制器能够对PID的参数进行在线自动调整,仿真结果表明,采用参数自适应模糊PID控制器后,控制系统的响应速度加快,超调量减小,过渡过程时间大大缩短,振荡次数少,具有较强的鲁棒性和良好的稳定性. 相似文献
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基于滑模观测器的永磁同步电机变结构鲁棒控制 总被引:1,自引:0,他引:1
提出一种由一个变结构控制器和一个滑模观测器组成的控制系统,用于永磁同步电机的无传感器鲁棒控制.首先利用Lyapunov稳定性原理分析得到观测器的收敛条件及自适应率,并证明了其稳定性,然后以转速误差为参量建立滑模面,构造出变结构速度控制器,推导出自适应速度控制律,并得到速度控制的参考电流和参考电压.该方案的控制性能不依赖于电机参数和干扰变化,具有较强的鲁棒性.仿真结果验证了该方案的有效性与正确性. 相似文献
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电力系统是强非线性的动态大系统,在运行中总要受到外部干扰和内部干扰的影响,从而对其稳定运行造成严重威胁.本文针对带有TCSC单机无穷大母线系统的三阶鲁棒模型,在考虑阻尼系数未知及系统受外部扰动的情况下,将自适应backstepping方法与非线性L2增益干扰抑制理论融合,构造出系统的存贮函数,并获得非线性自适应鲁棒控制器及参数替换律.所得控制器不仅能够保证系统状态有界,而且能够有效抑制干扰对系统输出的影响.通过对单机系统的仿真结果表明采用该方法的控制器优于传统的控制器. 相似文献
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一种新的鲁棒自适应控制器 总被引:1,自引:0,他引:1
本文通过引入估计误差符号信息的反馈来建立一种新的鲁棒自适应控制器,能确保存在有界外部干扰时Lyapunov函数对时间的导数的半负定性,从而确保了系统的稳定性,使系统具有较强的鲁棒性,理论分析与仿真结果表明,该鲁棒自适应控制器对有界外部干扰有较强的抑制能力,并且可以加快自适应初始阶段的收敛速度。 相似文献
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<正> 可擦除、可编程只读存贮器(EPROM)是一种半导体存贮器件,它具有集成度高、价格低廉、便于编程及能多次使用等优点。在顺序控制器中,采用这种器件取代传统的步进式和时序式顺序控制器中的矩阵板来进行工艺信息的记忆存贮,无疑对顺序控制器的结构和性能均有明显的改进。 相似文献
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本文提出了一种带有约束机构的并联柔索驱动转台,介绍该转台的机构构型,设计了一种利用模糊逻辑进行在线参数自适应的Fuzzy-PID控制器。该控制器能够对PID的参数进行在线自动调整,仿真结果表明,采用参数自适应模糊PID控制器后,控制系统的响应速度加快,超调量减小,过渡过程时间大大缩短,振荡次数少,具有较强的鲁棒性和良好的稳定性。 相似文献
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Chih-Min Lin Ya-Fu Peng 《Neural Networks, IEEE Transactions on》2005,16(3):636-644
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. 相似文献
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This paper analyses the application of two fault tolerant control schemes to a hydroelectric model developed in the Matlab and Simulink environments. The proposed fault tolerant controllers are exploited for regulating the speed of the Francis turbine included in the hydraulic system. The nonlinear behaviour of the hydraulic turbine and the inelastic water hammer effects are taken into account in order to develop a high-fidelity simulator of this dynamic plant. The first fault tolerant control solution relies on an adaptive control design, which exploits the recursive identification of a linear parametric time-varying model of the monitored system. The second scheme proposed uses the identification of a fuzzy model that is exploited for the reconstruction of the fault affecting the system under diagnosis. In this way, the fault estimation and its accommodation is possible. Note that these strategies, which are both based on identification approaches, are suggested for enhancing the application of the suggested fault tolerant control methodologies. These characteristics of the study represent key issues when on-line implementations are considered for a viable application of the proposed fault tolerant control schemes. The faults considered in this paper affect the electric servomotor used as a governor, the hydraulic turbine speed sensor, and the hydraulic turbine system, and are imposed both separately and simultaneously. Moreover, the complete drop of the rotational speed sensor is also analysed. Monte-Carlo simulations are also used for analysing the most important issues of the proposed schemes in the presence of parameter variations. Moreover, the performances achieved by means of the proposed solutions are compared to those of a standard PID controller already developed for the considered model. Finally, these strategies serve to highlight the potential application of the proposed control strategies to real hydraulic systems. 相似文献
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The conventional cerebellar model articulation controllers (CMAC) learning scheme equally distributes the correcting errors into all addressed hypercubes, regardless of the credibility of those hypercubes. This paper presents the adaptive fault-tolerant control scheme of non-linear systems using a fuzzy credit assignment CMAC neural network online fault learning approach. The credit assignment concept is introduced into fuzzy CMAC weight adjusting to use the learned times of addressed hypercubes as the credibility of CMAC. The correcting errors are proportional to the inversion of learned times of addressed hypercubes. With this fault learning model, the learning speed of fault can be improved. After the unknown fault is estimated, online, by using the fuzzy credit assignment CMAC, the effective control law reconfiguration strategy based on the sliding mode control technique is used to compensate for the effect of the fault. The proposed fault-tolerant controller adjusts its control signal by adding a corrective sliding mode control signal to confine the system performance within a boundary layer. The numerical simulations demonstrate the effectiveness of the proposed CMAC algorithm and fault-tolerant controller. 相似文献
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Chih-Min Lin Ya-Fu Peng 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2004,34(2):1248-1260
An adaptive cerebellar-model-articulation-controller (CMAC)-based supervisory control system is developed for uncertain nonlinear systems. This adaptive CMAC-based supervisory control system consists of an adaptive CMAC and a supervisory controller. In the adaptive CMAC, a CMAC is used to mimic an ideal control law and a compensated controller is designed to recover the residual of the approximation error. The supervisory controller is appended to the adaptive CMAC to force the system states within a predefined constraint set. In this design, if the adaptive CMAC can maintain the system states within the constraint set, the supervisory controller will be idle. Otherwise, the supervisory controller starts working to pull the states back to the constraint set. In addition, the adaptive laws of the control system are derived in the sense of Lyapunov function, so that the stability of the system can be guaranteed. Furthermore, to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Finally, the proposed control system is applied to control a robotic manipulator, a chaotic circuit and a linear piezoelectric ceramic motor (LPCM). Simulation and experimental results demonstrate the effectiveness of the proposed control scheme for uncertain nonlinear systems. 相似文献
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本文提出了一种基于小脑模型关节控制器(CMAC)的评论–策略家算法,设计不依赖模型的跟踪控制器,来解决机器人的跟踪问题.该跟踪控制器包含位置控制器和角度控制器,其输出分别为线速度和角速度.位置控制器由评价单元和策略单元组成,每个单元都采用CMAC算法,按改进δ学习规则在线调整权值.策略单元产生控制量;评判单元在线调整策略单元学习速率.以双轮驱动自主移动机器人为例,与固定学习速率CMAC做比较,仿真数据表明,基于CMAC的评论–策略家算法的跟踪控制器具有跟踪速度快,自适应能力强,配置参数范围宽,不依赖数学模型等特点. 相似文献
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针对具有强非线性、高度耦合以及参数不确定性特点的小型无人直升机系统,提出一种基于小脑模型关节控制器(Cerebellar Model Articulation Control,CMAC)神经网络的自适应反步控制方法,该方法采用小脑模型关节控制器神经网络在线学习系统不确定性以及反步控制中各阶虚拟控制量的导数信息,设计鲁棒控制项克服CMAC神经网络在线学习系统不确定性的误差,控制律由反步法回归递推得到。仿真结果表明,在模型参数不确定和存在较大误差的情况下,所设计的控制律具有理想的姿态跟踪性能以及良好的鲁棒性。 相似文献
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本文以成都拜尔电力设备有限公司自行研发的以贝加莱PCC为控制核心的水轮机调速器为例,从水轮机调速器的原理、硬件配置和软件结构来论述和探讨了怎样通过PCC技术来实现调速器的各种功能,以及它与传统调速器的区别和所具有的优势。 相似文献
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应用信度分配的模糊CMAC实现非线性系统的容错控制 总被引:4,自引:1,他引:4
The adaptive fault-tolerant control scheme of dynamic nonlinear system based on the credit assigned fuzzy CMAC neural network is presented. The proposed learning approach uses the learned times of addressed hypercubes as the credibility, the amounts of correcting errors are proportional to the inversion of the learned times of addressed hypercubes. With this idea, the learning speed can indeed be improved. Based on the improved CMAC learning approach and using the sliding control technique, the effective control law reconfiguration strategy is presented. Thesystem stability and performance are analyzed under failure scenarios. The numerical simulation demonstrates the effectiveness of the improved CMAC algorithm and the proposed fault-tolerant controller. 相似文献