共查询到18条相似文献,搜索用时 187 毫秒
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采用模糊动态模型对连续时间非线性系统进行模糊控制,对闭环模糊系统的稳定性进行分析,并给出系统化的控制器设计程序,在一系列局部模型通过模糊隶属函数连接得到的连续的全局模型中,全面考虑其它关联子系统对标称线性系统的摄动,并利用向量Lyapunov函数的概念和方法,得到了闭环模糊系统稳定的充分条件;仿真例子验证了该设计方法的正确性。 相似文献
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模糊控制的系统化设计和稳定性分析 总被引:13,自引:2,他引:11
给出了一种模糊控制系统的系统化设计方法,它采用一组局部T-S模糊模型来表
示模糊系统,对每个局部模型,利用状态反馈进行控制器设计,最后给出了全局模糊系统的稳
定性分析.通过对一个典型的非线性球-棒控制系统的仿真研究,表明该方法是有效的,它的
性能指标优于现有文献的结果. 相似文献
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针对一般形式的非线性系统,提出一种基于模糊双曲模型(FHM)的积分滑模控制器设计方法.利用模糊双曲模型来表述这类连续非线性系统.构建出积分滑模面,利用线性矩阵不等式(LMI)方法得到滑模动态渐近稳定的充分条件.设计了积分滑模控制器,保证了系统的状态轨迹能够在有限时间内到达滑模面上并且保持在它上面运动.仿真结果表明了该方法的有效性. 相似文献
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针对非线性系统难以精确建模与动态性能分析的基本控制问题,基于模糊动态模型把布尔网络系统理论推广到非线性布尔网络系统,建立了模糊动态布尔网络控制系统的模型。引入模糊动态模型,对非线性布尔网络进行模糊建模,分别建立了非线性布尔网络系统的局部模型和全局模型。从系统的局部意义和全局意义上,对系统进行了能控性、能观性、稳定性等动态性能分析。最后,以多输入多输出的非线性布尔网络系统实例为具体研究对象,建立了系统的局部模型和全局模型,并对动态性能进行了仿真分析,得到了实验结果。实验结果表明,模糊动态布尔网络控制系统对非线性布尔网络系统的建模是有效的,动态性能分析是合理的,对模糊动态布尔网络控制系统的进一步分析有重要意义。 相似文献
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针对一类利用T-S模糊模型近似描述的不确定非线性系统,给出了一种具有鲁棒极点配置功能的模糊控制器和模糊状态观测器的设计方法.首先,利用并行分配补偿(PDC)设计思想和基于线性矩阵不等式(LMI)的鲁棒极点配置理论,得到了使整个闭环系统全局渐近稳定并满足希望的动态性能的充分条件.然后将这些条件转化为标准的LMI问题.最后将该设计方法应用于倒立摆的平衡控制中,验证了本方法的有效性. 相似文献
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该文对非线性系统的建模采用Cao-Ress(C-R)模糊模型,并用卡尔曼滤波算法在线辨识模糊模型的结论参数,从而减少了参数辨识的数量和避免了矩阵的求逆运算,然后在每一个采样点对该系统进行局部动态线性化,根据得到的系统线性化模型对系统采取广义预测控制(GPC)方法得到当前的控制动作。仿真结果表明了该方法的有效性。 相似文献
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This paper considers the control of a linear drive system with friction and disturbance compensation. A stable adaptive controller integrated with fuzzy model-based friction estimation and switching-based disturbance compensation is proposed via Lyapunov stability theory. A TSK fuzzy model with local linear friction models is suggested for real-time estimation of its consequent local parameters. The parameters update law is derived based on linear parameterization. In order to compensate for the effects resulting from estimation error and disturbance, a robust switching law is incorporated in the overall stable adaptive control system. Extensive computer simulation results show that the proposed stable adaptive fuzzy control system has very good performances, and is potential for precision positioning and trajectory tracking control of linear drive systems. 相似文献
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Wen-Shyong Yu Chih-Jen Sun 《Fuzzy Systems, IEEE Transactions on》2001,9(3):413-425
A fuzzy model based adaptive control algorithm for a class of continuous-time nonlinear dynamic systems is presented. The fuzzy model consisting of a set of linear fuzzy local models that are combined using a fuzzy inference mechanism is used to model a class of nonlinear systems. Each fuzzy local model represents a linearized model corresponding to the operating point of the controlled nonlinear system. The proposed control algorithm employs the fuzzy controller that is designed by considering the linear state feedback controller corresponding to the fuzzy local model with the maximum weight and the switching-σ modification adaptive controller to adaptively compensate for the plant nonlinearities. Stability robustness of the closed-loop system is analyzed in Lyapunov sense. It is shown, that the proposed control algorithm guarantees global stability of the system with the output of the system approaching the origin if there are no disturbances and uncertainties, converging to the neighborhood of the origin for all realizations of uncertainties and disturbances. The simulation examples for controlling inverted pendulum system are given to illustrate the effectiveness of the proposed method 相似文献
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针对一类非线性系统,把模糊T-S模型和自适应模糊逻辑系统两类模糊逻辑方式结合起来,提出了一种基于观测器的控制方案.首先,应用模糊T-S模型对非线性系统建模,设计观测器来观测系统状态;由线性矩阵不等式得到模糊模型的控制律.其次,应用自适应模糊逻辑系统作为补偿器来补偿建模误差.证明了闭环系统满足期望的性能.仿真结果表明了该方案的可行性. 相似文献
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《Fuzzy Systems, IEEE Transactions on》2005,13(4):531-543
This paper presents an observer based$H_infty$ output feedback synthesis method for discrete time fuzzy dynamic systems based on a piecewise Lyapunov function. The basic idea of the approach is to design an observer based piecewise linear output feedback control law to guarantee the global stability with$H_infty$ performance of the resulting closed-loop fuzzy control systems. It is shown that the controller parameters can be obtained by solving a set of linear matrix inequalities (LMIs) that are numerically feasible with commercially available software. Application to control chaotic systems is given to illustrate the effectiveness and advantages of the proposed method. 相似文献
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Chih-Lyang Hwang Li-Jui Chang 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2007,37(6):1471-1485
In this paper, a partially known nonlinear dynamic system with time-varying delays of the input and state is approximated by N fuzzy-based linear subsystems described by a state-space model with average delay. To shape the response of the closed-loop system, a set of fuzzy reference models is established. Similarly, the same fuzzy sets of the system rule are employed to design a fuzzy neural-based control. The proposed control contains a radial-basis function neural network to learn the uncertainties caused by the approximation error of the fuzzy model (e.g., time-varying delays and parameter variations) and the interactions resulting from the other subsystems. As the norm of the switching surface is inside of a defined set, the learning law starts; in this situation, the proposed method is an adaptive control possessing an extra compensation of uncertainties. As it is outside of the other set, which is smaller than the aforementioned set, the learning law stops; under this circumstance, the proposed method becomes a robust control without the compensation of uncertainties. A transition between robust control and adaptive control is also assigned to smooth the possible discontinuity of the control input. No assumption about the upper bound of the time-varying delays for the state and the input is required. However, two time-average delays are needed to simplify the controller design: 1) the stabilized conditions for every transformed delay-free subsystem must be satisfied; and 2) the learning uncertainties must be relatively bounded. The stability of the overall system is verified by Lyapunov stability theory. Simulations as compared with a linear transformed state feedback with integration control are also arranged to consolidate the usefulness of the proposed control. 相似文献
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针对连续非线性多智能体系统的全局最优协同控制问题,本文提出了模糊输出反馈和逆最优方法的分布式一致性最优控制律和相应的控制策略.首先,通过一种区间2型T-S (interval type 2 Takagi-Sugeno IT2 T-S)模糊模型将非线性系统等价转化为线性系统.其次,基于逆最优方法设计了全局最优协同控制律和相应的模糊输出反馈控制策略,智能体间仅仅通过局部通信,即可实现拓扑切换下非线性多智能体系统的二次性能全局最优控制,且系统的收敛速度大大提高.基于局部稳定性理论给出了全局逆最优控制的充要条件.最后,通过MATLAB算例验证所提方法的正确性和可行性. 相似文献