共查询到18条相似文献,搜索用时 531 毫秒
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针对一类单输入单输出(SISO)非仿射非线性系统控制方向未知时出现的控制器奇异问题,提出了一种间接自适应模糊控制方案.利用中值定理将非仿射系统转化为仿射系统,通过模糊逻辑系统逼近该仿射系统中的未知函数,并构造模糊控制器,同时利用Lyapunov稳定性定理设计自适应律,最终克服了控制器的奇异问题;在此基础上,通过构造观测器估计跟踪误差,设计输出反馈自适应模糊控制器,解决了状态不可测时系统控制器设计难题,采用Lyapunov稳定性定理证明控制器能使得跟踪误差收敛同时闭环系统所有信号均有界.仿真结果验证了所设计控制方案的可行性与有效性. 相似文献
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针对受到扰动的变机翼后掠角近空间飞行器,研究一类基于多模型切换的多输入多输出非线性系统的模糊自适应鲁棒控制器的设计问题.通过构造公共Lyapunov函数设计系统的控制器,采用动态面控制方法避免了控制器设计中的计算膨胀问题,利用自适应模糊系统和鲁棒控制项在线消除系统中的未知干扰影响.仿真结果表明了该方法的有效性. 相似文献
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动态不确定非线性系统直接自适应模糊backstepping控制 总被引:3,自引:0,他引:3
对一类单输入单输出动态不确定非线性系统,提出一种直接自适应模糊backstepping和小增益相结合的控制方法.设计中,首先用模糊逻辑系统逼近虚拟控制器:其次把自适应模糊控制和backstepping控制设计技术相结合.给出了直接自适应模糊控制设计方法.最后基于Lyapunov函数和小增益方法证明了整个闭环系统的稳定性.仿真实例进一步验证了所提方法的有效性. 相似文献
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非线性大系统的分散自适应模糊控制* 总被引:4,自引:1,他引:3
本文针对非线性大系统,利用模糊系统的逼近能力,提出了一种分散自适应模糊控制器设计的系统方法。控制结构中采用分散模糊系统去自适应补偿过程不确定性,同时用模糊控制器的输出代替常规变结构控制律中的符号函数。利用李亚普诺夫理论,证明了控制算法是全局稳定的,跟踪误差可收敛到零的一个领域内。 相似文献
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基于模糊逻辑系统具有充分利用语言信息和逼近连续函数性质的思想,分析研究了一类非线性不确定复杂系统的自适应控制问题.利用系统的数学模型和模糊逻辑系统对不确定性的输出信息,设计出了复杂系统的分散自适应鲁棒控制器和模糊逻辑系统参数估计的自适应律,在较弱的假设条件下,证明了这种控制器使被控系统的状态及参数估计误差一致终极有界.仿真实例表明,所提出的方法是有效的. 相似文献
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Tao C.W. 《IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans : a publication of the IEEE Systems, Man, and Cybernetics Society》2002,32(5):614-620
In this paper, a new adaptive fuzzy Proportional-Integral (of a modified error function)-Derivative (PIMD) controller is designed for systems with uncertain deadzones. Instead of using the summation of the system output error to be one of the input variables, the fuzzy mechanism in PIMD controller takes the summation of a proposed error function as one essential part of the output fuzzy singleton. Together, with the linearly combined error and difference of the error as the only input variables, the complexity reduced fuzzy mechanism of the fuzzy PIMD controller is constructed. The adaptation processes are provided to determine the parameters of the PIMD controller to reduce the overshoot and to accelerate the system with deadzone to the desired output. The fuzzy PIMD controller is indicated to be flexible to the variations of deadzone parameters. Also, the proposed fuzzy PIMD controller is flexible to the change of deadzone model to contain jump discontinuity points. Moreover, the fuzzy PIMD controller can perform well for the system with time-varying deadzone model. Simulation results are included to indicate the effectiveness of the adaptive fuzzy PIMD controller. 相似文献
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This paper focuses on the problem of direct adaptive fuzzy control for nonlinear strict-feedback systems with time-varying delays. Based on the Razumikhin function approach, a novel adaptive fuzzy controller is designed. The proposed controller guarantees that the system output converges to a small neighborhood of the reference signal and all the signals in the closed-loop system remain bounded. Different from the existing adaptive fuzzy control methodology, the fuzzy logic systems are used to model the desired but unknown control signals rather than the unknown nonlinear functions in the systems. As a result, the proposed adaptive controller has a simpler form and requires fewer adaptation parameters. 相似文献
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自适应神经模糊推理结合PID控制的并联机器人控制方法 总被引:1,自引:0,他引:1
针对6自由度液压驱动并联机器人的精确控制问题,提出一种结合自适应神经模糊推理系统(ANFIS)和比例积分微分(PID)控制的机器人控制方法。首先,利用浮动坐标系描述法(FFRF)来模拟机器人柔性组件,并构建并联机器人的拉格朗日动力学模型。然后,根据模糊推理中的模糊规则来自适应调整PID控制器参数。最后,利用神经自适应学习算法使模糊逻辑能计算隶属度函数参数,从而使模糊推理系统能追踪给定的输入和输出数据。将该控制器与传统PID控制器、模糊PID控制器进行比较,结果表明,ANFIS自整定PID控制器大大减小了末端器位移误差,能很好的控制并联机器人末端机械手的运动。 相似文献
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一类非线性离散系统的直接自适应模糊控制 总被引:1,自引:0,他引:1
针对一类含延迟非线性离散系统,提出了一种直接自适应模糊控制器设计的新方案.将系统用T-S模糊模型来表示,并基于并行分布补偿(PDC)基本思想设计了一种具有未知参数的模糊控制器,同时采用梯度下降算法对该控制器的参数进行在线辨识.通过输入到状态稳定(ISS)方法,证明了系统输出和参考输出的误差有界且满足一定的平均性能.仿真表明本方法的有效性. 相似文献
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Intelligent systems may be viewed as a framework for solving the problems of nonlinear system control. The intelligence of the system in the nonlinear or changing environment is used to recognize in which environment the system currently resides and to service it appropriately. This paper presents a general methodology of adaptive control based on multiple models in fuzzy form to deal with plants with unknown parameters which depend on known plant variables. We introduce a novel model‐reference fuzzy adaptive control system which is based on the fuzzy basis function expansion. The generality of the proposed algorithm is substantiated by the Stone‐Weierstrass theorem which indicates that any continuous function can be approximated by fuzzy basis function expansion. In the sense of adaptive control this implies the adaptive law with fuzzified adaptive parameters which are obtained using Lyapunov stability criterion. The combination of adaptive control theory based on models obtained by fuzzy basis function expansion results in fuzzy direct model‐reference adaptive control which provides higher adaptation ability than basic adaptive‐control systems. The proposed control algorithm is the extension of direct model‐reference fuzzy adaptive‐control to nonlinear plants. The direct fuzzy adaptive controller directly adjusts the parameter of the fuzzy controller to achieve approximate asymptotic tracking of the model‐reference input. The main advantage of the proposed approach is simplicity together with high performance, and it has been shown that the closed‐loop system using the direct fuzzy adaptive controller is globally stable and the tracking error converges to the residual set which depends on fuzzification properties. The proposed approach can be implemented on a wide range of industrial processes. In the paper the foundation of the proposed algorithm are given and some simulation examples are shown and discussed. © 2002 Wiley Periodicals, Inc. 相似文献
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This paper is concerned with the problem of adaptive fuzzy output tracking control for a class of nonlinear pure-feedback stochastic systems with unknown dead-zone. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinearities, then a novel adaptive fuzzy tracking controller is designed by using backstepping technique. The control scheme is systematically derived without requiring any information on the boundedness of dead-zone parameters (slopes and break-points) and the repeated differentiation of the virtual control signals. The proposed adaptive fuzzy controller guarantees that all the signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighbourhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme. 相似文献
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Hafedh Abid Mohamed Chtourou Ahmed Toumi 《International Journal of Control, Automation and Systems》2009,7(6):982-991
In this paper we are interested in robust adaptive fuzzy control of nonlinear SISO systems in the presence of parametric uncertainties.
The plant model structure is represented by the Takagi-Sugeno (T-S) type fuzzy system. An indirect adaptive fuzzy controller
based on model reference control scheme is proposed to provide asymptotic tracking of reference signal. The controller parameters
are computed at each time. The plant state tracks asymptotically the state of the reference model for any bounded reference
input signal. Inverted pendulum and mass spring damper are used to check the performance of the proposed controller. 相似文献
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Hafedh Abid Ahmed Toumi 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2016,20(2):649-659
In this paper, we propose an adaptive fuzzy controller for a class of nonlinear SISO time-delay systems. The plant model structure is represented by a Takagi–Sugeno (T–S) type fuzzy system. The T–S fuzzy model parameters are adjusted online. The proposed algorithm utilizes the sliding surface to adjust online the parameters of T–S fuzzy model. The controller is based on adjustable T–S fuzzy parameters model and sliding mode theory. The stability analysis of the closed-loop system is based on the Lyapunov approach. The plant state follows asymptotically any bounded reference signal. Two examples have been used to check performances of the proposed fuzzy adaptive control scheme. 相似文献