基于模糊逻辑的连续滑模控制

针对一类具有不确定性的非线性系统，根据滑模控制原理，提出了一种基于模糊逻辑的连续滑模控制设计方法。由于使用了适当的模糊逻辑切换，避免了滑模控制所固有的颤动现象．仿真结果表明，本文设计的模糊控制，对模型不确定性和外来干扰具有较强的鲁棒性和良好的跟踪性能．     

AUV深度的模糊神经网络滑模控制

本文设计了一个模糊神经网络滑模变结构控制器，通过模糊神经网络对滑模控制律 的控制增益进行在线调整，并在海浪干扰条件下，用此控制器对AUV进行深度控制．仿真结 果验证了该智能控制方法具有很好的控制性能和鲁棒牲．     

基于模糊逻辑的滑模控制设计方法

针对一类具有不确定性的单输入非线性系统，根据滑模控制原理。采用趋近律方法优化的滑模控制设计方法，以满足控制系统的鲁棒性和趋近运动品质的要求；同时根据模糊理论将切换函数模糊化，并且通过模糊规则自适应调整切换函数的模糊量化因子，以消除变结构控制系统固有的抖振和进一步改善系统偏差。仿真结果表明．设计的模糊滑模系统，具有对模型不确定性和外来干扰较强的鲁棒性以及良好的跟踪性能。避免了系统固有的颤动现象，控制的效果良好，性能满意；可应用于此类不确定非线性系统的设计综合问题。     

汽车线控转向系统的模糊滑模控制研究

针对汽车线控转向系统结构复杂、模型参数具有不确定性以及存在多种干扰源的问题,设计了一种模糊滑模控制方法。基于滑模控制算法,设计了标称控制器和滑模补偿控制器。通过滑模补偿控制器,消除了系统参数的不确定性和路面条件变化对转向性能的影响。采用模糊逻辑设计滑模边界层,削弱了滑模控制中的抖振问题。仿真结果表明,当路面条件发生变化时,模糊滑模控制能有效削弱滑模控制的抖振现象,具有较好的响应速度和鲁棒性。     

基于滑模产生条件的模糊滑模控制及其稳定性分析

通过将表示滑模运动特征的代数值作为模糊系 统的一维输入，本文简化了模糊滑模控制的系统 结构，从根本上消除了规则的组合爆炸， 并针对一类特定系统进行了稳定性分析．PM同步电机位置伺 服控制的仿真表明了这种控制 算法的有效性和简便性．     

基于模糊逻辑的连续滑模控制

基于模糊逻辑的连续滑模控制东南大学自动化所张天平，冯纯伯针对一类具有不确定性的非线性系统，根据滑模控制原理，提出一种基于模糊逻辑的连续滑模控制设计方法。由于使用了适当的模糊逻辑切换，从而避免了滑模控制所固有的颤动现象。仿真结果表明，本文设计的模糊控制...     

模糊变结构控制的旋转倒立摆系统设计

本文针对非线性、多变量、强耦合的旋转倒立摆系统，利用模糊控制与滑模变结构控制相结合设计了一种模糊变结构控制器．该控制器既保持了滑模变结构控制的快速性和鲁棒性，又能较好地消除单纯采用滑模变结构所产生的抖振问题。仿真结果表明，模糊变结构控制算法能够实现倒立摆的平衡姿态控制，抖振现象基本消除且具有很强的鲁棒性。     

基于上界估计的变参数Lorenz系统模糊滑模控制

传统滑模控制设计方法根据系统不确定性上界函数得到的切换增益,不能随着受控状态的变化而相应变化,存在滑模控制量反应不够及时的问题,并且需要预先知道系统不确定性的上界函数,对滑模控制应用到混沌系统控制当中造成了限制.针对变参数的Lorenz混沌系统提出了一种模糊滑模控制方法,控制系统到达平衡状态.模糊控制器的输入为滑模面S,通过设计合理的输入输出隶属度函数以及模糊规则,输出的μ值能在线调节滑模控制切换量中的切换增益,有效地解决了滑模控制量反应不够及时的问题;另外设计了状态观测器,对系统的不确定性函数进行了估计.仿真实验结果验证了所提出的模糊滑模控制有着良好的控制效果.     

模糊滑模控制研究综述

本文介绍了90年代以来将模糊逻辑和滑模控制相结合的研究工作,着重描述了模糊控制和滑模控制的相似性、启发式模糊滑模控制、直接和间接自适应模糊滑模控制、模糊神经网络在滑模控制中的应用等方面的原理和方法,分析了它们的特点和联系,本文最后还展望了这一领域的研究方向.     

一类非线性不确定系统的非奇异Terminal滑模控制

针对一类二阶非线性系统提出新的Terminal滑模控制面以克服传统的Terminal滑模控制的奇异问题，同时确保系统从任何初始状态能在有限时间内收敛至平衡点．进一步考虑系统参数摄动和外界扰动等不确定性因素上界的未知性，用Lyapunov稳定性方法给出了一个带有未知性上界参数估计的自适应非奇异Terminal滑模控制（NTSM）控制．最后通过实例比较三种滑模控制方法，仿真结果验证了非奇异Terminal滑模控制能克服传统的Terminal滑模控制的奇异问题，并说明了自适应非奇异Terminal滑模控制的有效性和可行性．     

Adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties

A new design approach of an adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties is presented in this paper. A fuzzy terminal sliding mode controller is designed to retain the advantages of the terminal sliding mode controller and to reduce the chattering occurred with the terminal sliding mode controller. The sufficient condition is provided for the uncertain system to be invariant on the sliding surface. The parameters of the output fuzzy sets in the fuzzy mechanism are adapted on-line to improve the performance of the fuzzy sliding mode control system. The bounds of the uncertainties are not required to be known in advance for the presented adaptive fuzzy sliding mode controller. The stability of the fuzzy control system is also guaranteed. Moreover, the chattering around the sliding surface in the sliding mode control can be reduced by the proposed design approach. Simulation results are included to illustrate the effectiveness of the proposed adaptive fuzzy terminal sliding mode controller.     

PHANTOM Omni机器人的自适应模糊滑模控制

针对PHANTOM Omni机器人的位置轨迹跟踪问题,采用了一种基于模糊逻辑的自适应模糊滑模控制方案。利用滑模控制中的切换函数作为输入,根据模糊系统的逼近能力设计控制器,并基于李雅谱诺夫方法设计自适应律对控制器所需参数进行实时调节。仿真中将其与传统的滑模控制进行了比较,仿真结果表明：自适应模糊滑模控制能使PHANTOM Omni机器人更好地实现期望的位置轨迹跟踪并有效地减轻抖振现象,从而证明了该方法在PHANTOM Omni机器人上实施的可行性。     

基于自适应模糊滑模观测器的永磁同步电机无传感器矢量控制

针对传统滑模观测器(SMO)存在的抖振及相位延迟问题,提出一种自适应模糊滑模观测器来实现永磁同步电机(PMSM)无传感器控制.根据Lyapunov稳定性定理构建自适应模糊滑模观测器,以保证系统的稳定性.通过分析滑模增益对系统抖振的影响设计模糊控制系统,从而实现对滑模增益的动态调整,削弱抖振现象,提高系统的鲁棒性.建立反电动势观测器代替低通滤波器,避免相位延迟,从而提高系统的稳定性及准确跟踪性.仿真结果验证了所提出方法的可行性.     

基于模糊双线性模型的连续搅拌反应釜滑模控制

主要对连续搅拌反应釜系统(CSTR)的滑模控制问题进行研究;该系统的模型可由Takagi-Sugeno (T-S)模糊双线性模型进行描述,基于该模糊双线性模型,给出滑模控制方法;在之前学者的研究成果上对线性滑模面进行改进,构造积分滑模面,由此设计出的等效控制量与切换控制量,可以保证系统的控制精度;通过对其进行稳定性研究,得到全局稳定的充分条件,并求出滑模面的控制器参数;同时,构造7条模糊规则,采用模糊化方法对切换增益项进行模糊推理,使整体控制量平滑化,也避免系统状态出现抖振现象,实现实际可操作性;最后,连续搅拌反应釜的仿真验证了控制方法的有效性.     

Adaptive fuzzy sliding mode controller for linear systems with mismatched time-varying uncertainties

A new design approach for an adaptive fuzzy sliding mode controller (AFSMC) for linear systems with mismatched time-varying uncertainties is presented. The coefficient matrix of the sliding function can be designed to satisfy a sliding coefficient matching condition provided time-varying uncertainties are bounded. With the sliding coefficient matching condition satisfied, an AFSMC is proposed to stabilize the uncertain system. The parameters of output fuzzy sets in the fuzzy mechanism are on-line adapted to improve the performance of the fuzzy sliding mode control system. The bounds of uncertainties are not required to be known in advance for the AFSMC. Stability of the fuzzy control system is guaranteed and the system is shown to be invariant on the sliding surface. Moreover, chattering around the sliding surface in sliding mode control can be reduced by the proposed design approach. Simulation results are included to illustrate the effectiveness of the proposed AFSMC.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

一种新的自适应模糊滑模控制器设计方法

对一类非线性系统提出一种新的自适应模糊滑模控制器设计方法。将自适应模糊控制与滑模控制有效地结合在一起,先用滑模控制使跟踪误差进入边界层内,然后启动自适应模糊控制器。该控制器可消除滑模控制器中出现的抖振,并可在存在模糊逻辑系统逼近误差情况下使系统跟踪误差小于预先给定的任意常数。仿真算例验证了所提出方法的有效性。     

基于自适应模糊滑模控制的船舶航向控制器设计

针对船舶运动系统中固有的非线性、模型不确定性和风、浪、流等的干扰.提出了自适应模糊滑模控制(AFSMC)策略解决船舶的航向控制问题.通过采用模糊逻辑系统逼近系统未知函数,将滑模控制技术与自适应模糊控制技术相结合,设计了船舶航向AFSMC控制器.在滑模边界层内应用PI (proportional-integral)控制代替滑模控制中的切换项,削弱了滑模控制带来的抖振现象.借助李亚普诺夫函数证明了船舶运动系统中的信号都一致有界并利用Barbalat引理证明了跟踪误差渐近收敛到零.在参数摄动和外界干扰情况下进行了航向保持与改变仿真试验,采用AFSMC控制器得到了与无摄动和无干扰情况下相似的输出响应.实验结果表明,所提控制器能有效地处理系统不确定性和外界干扰,控制性能良好,具有很强的鲁棒性.     

Improving asynchronous motor speed and flux loop control by using hybrid fuzzy-SMC controllers

This paper presents a new method combining sliding mode control (SMC) and fuzzy logic control (FLC) to enhance the robustness and performance for a class of non-linear control systems. This fuzzy sliding mode control (FSMC) is developed for application in the area for controlling the speed and flux loops of asynchronous motors. The proposed control law can solve those problems associated with the conventional control by sliding mode control, such as high current, flux and torque chattering, variable switching frequency and variation of parameters, in which a robust fuzzy logic controller replaces the discontinuous part of the classical sliding mode control law. Simulation results of the proposed FSMC technique on the speed and flux rotor controllers present good dynamic and steady-state performances compared to the classical SMC in terms of reduction of the torque chattering, quick dynamic torque response and robustness to disturbance and variation of parameters.     

Parallel Distributed Fuzzy Sliding Mode Control for Nonlinear Mismatched Uncertain Systems

A new design approach of a parallel distributed fuzzy sliding mode controller for nonlinear systems with mismatched time varying uncertainties is presented in this paper. The nonlinear system is approximated by the Takagi–Sugeno fuzzy linear model. The approximation error between the nonlinear system and the fuzzy linear model is considered as one part of the uncertainty in the uncertain nonlinear system. The time varying uncertainties are assumed to have the format which enables the design of the coefficient matrix of the sliding function to satisfy a sliding coefficient matching condition. With the sliding coefficient matching condition satisfied, a parallel distributed fuzzy sliding mode controller (PDFSC) is designed. The stability and the sliding mode of the fuzzy sliding control system are guaranteed. Also, the nonlinear system is shown to be invariant on the sliding surface. Moreover, the chattering around the sliding surface in the sliding mode control can be reduced by the proposed design approach. Simulation results are included to illustrate the effectiveness of the proposed fuzzy sliding mode controller. This work is partly supported by the the R.O.C. National Science Council through Grant NSC93-2213-E-197-004.