基于不确定T-S模型的模糊滑模自适应控制

提出一种不确定T-S模型的模糊滑模自适应控制方法。通过变换将该模型转换成3个组成部分：线性标称系统,已知非线性部分和未知不确定部分。针对它们设计3个控制器,其作用分别为：强迫系统沿着滑模面运动,消除已知扰动对线性标称系统的影响,克服不确定扰动(采用模糊滑模自适应控制,无需知道不确定的界限)。该方法无需求正定矩阵就能保证系统全局稳定。     

多关节机器人的自适应模糊滑模控制

针对多关节机械臂轨迹跟踪控制,提出了一种基于全局快速终端滑模面的自适应模糊滑模控制方法。该方法通过设计合适的自适应律,采用模糊自适应控制调节滑模控制的切换控制增益,实现了对建模误差和不确定干扰的自动跟踪,削弱了抖振。系统不需要对建模误差和干扰进行预估计,并且通过对控制器结构的简化,降低了模糊控制器的维数,减少了计算量。利用李亚普诺夫定理证明了控制系统的稳定性,仿真结果表明了其有效性。     

自适应模糊全局快速Terminal滑模控制方法

提出了一种自适应模糊全局快速Terminal滑模控制方法,在参数不确定性和外干扰情况下,为解决系统的非线性不确定性提供了一种新途径。与传统模糊Terminal滑模控制相比,通过采用模糊逻辑系统来逼近未知系统函数和开关项;鲁棒自适应律用来减小逼近误差,从而有效降低抖振;证明了该控制方案的稳定性,并将该方案应用在倒立摆系统中。仿真结果验证了该方案的有效性。     

直线同步电动机磁悬浮系统的自适应模糊滑模控制

提出一种自适应模糊滑模控制方法用以提高可控励磁直线同步电动机(controllable excitation linear synchronous motor, CELSM)磁悬浮控制系统的性能.根据CELSM的特定结构和运行机理,建立CELSM磁悬浮系统的数学模型,包括励磁回路的电压方程、磁悬浮力方程和运动方程;设计积分滑模面和分段趋近律,系统状态轨迹可以根据距滑模面的距离自动切换趋近速度,以很小的斜率穿越滑模面,减小系统的抖振,推导出相应的滑模控制器;为了克服不确定性扰动对系统的影响,设计自适应律使自适应模糊系统对不确定性扰动进行实时估计,用该估计值进行前馈补偿控制,减小控制律中的切换增益和系统的抖振,进一步推导出自适应模糊滑模控制器;用Matlab对控制系统进行仿真,仿真结果表明,采用自适应模糊滑模控制的CELSM磁悬浮系统的性能得到改善.     

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控制的分数阶混沌系统的投影同步

基于模糊控制理论和滑模控制理论以及自适应控制理论,研究了一类含有外部扰动的不确定分数阶混沌系统的混合投影同步问题.提出了一种自适应模糊滑模控制的分数阶混沌系统投影同步方法.模糊逻辑系统用来逼近未知的非线性函数和外部扰动,并且对逼近误差采用了自适应控制,同时构造了一种具有较强鲁棒性的分数阶积分滑模面.应用分数阶Barbalat引理设计了自适应模糊滑模控制器和参数自适应律.最后数值仿真结果验证了所提控制方法的有效性.     

一种新的模糊滑模控制器设计方法

针对具有较大且不可观测外界干扰的一类不确定系统,提出一种新的模糊滑模控制器设计方法.首先基于模糊滑模控制原理,引入全局快速终端滑模控制,使系统在有限时间内达到稳态;然后构造以李雅普诺夫函数导数的绝对值为补偿的自适应干扰估计项,对外界干扰进行准确估计,进而提出一种双层递阶指数趋近全局快速终端模糊滑模控制器,通过指数趋近率来调节滑模面的动态品质,该控制器能快速收敛到稳定状态,且有效消除控制器的抖振情况;最后通过仿真算例验证所提方法的有效性.     

基于模糊控制的高超声速飞行器二阶滑模姿态控制

考虑高超声速飞行器飞行过程中气动参数变动导致的不确定,将模糊控制与二阶滑模控制相结合,形成自适应模糊二阶滑模控制器,用于控制高超声速飞行器姿态的飞行系统中.依据奇异摄动理论,设计快速和慢速双闭环系统控制角速率和姿态角.设计二阶滑模控制器用于有效地衰减抖振,同时对姿态角指令实现准确和快速跟踪.采用自适应模糊逻辑逼近高超声速飞行器动力学和运动学模型中的不确定部分,以对控制器进行有效补偿,基于Lyapunov稳定性理论,推导模糊规则参数的自适应律,确保整个闭环控制系统的稳定.仿真结果表明,所提出的高超声速飞行器的自适应模糊滑模控制系统能够有效抑制气动参数摄动的影响,对姿态角指令有较好的跟踪性能.     

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.     

Adaptive fuzzy sliding mode control for flexible satellite

The adaptive fuzzy sliding mode control is applied to the attitude stabilization of flexible satellite. The detailed design procedure of the fuzzy sliding mode control system is presented. The adaptive fuzzy control is utilized to approach the equivalent control of sliding mode control and the adaptive law is derived. The hitting control, which guarantees the stability of the control system, is developed. In order to attenuate the chattering phenomena, fuzzy rules are employed to smooth the hitting control. Simulation results show that precise attitude control is accomplished based on the proposed method.     

一类非线性系统的间接自适应模糊滑模控制

基于启发式知识的模糊控制是一种解决非线性系统控制问题的有效方法。然而其设计缺乏系统性,并且系统的稳定性和鲁棒性难以保证。本文利用滑模控制的概念和Lyapunov综合方法提出一种针对一类非线性系统的间接自适应模糊滑模控制（IAFSMC）方法。仿真研究表明即使在缺少系统先验知识和不确定性干扰的情况下,系统性能也十分理想。     

基于非奇异快速终端滑模的轧机液压伺服位置系统反步控制

针对具有非线性、参数不确定性和未知负载扰动的非对称缸轧机液压伺服位置系统,提出一种基于模糊自适应观测器和非奇异快速终端滑模面的反步控制方法.首先,基于非奇异快速终端滑模面和双幂次趋近律完成非对称缸轧机液压伺服位置系统反步控制器的设计,并通过构造二阶滑模滤波器对虚拟控制量的微分信号进行估计,有效地避免了反步控制中的微分爆炸现象;然后,选用模糊自适应观测器对系统的不确定项进行逼近估计,并将输出的估计值引入到设计的控制器中进行补偿,有效地提高了系统的跟踪控制精度,且分析表明,所提出的控制方法能够保证闭环系统全局渐近稳定;最后,基于某650mm可逆冷带轧机液压伺服位置系统的实际参数进行仿真研究,并与常规线性滑模控制方法相比较,结果验证了所提出方法能够有效提高系统在整个全局过程的收敛速度和鲁棒稳定性.     

GA-based modified adaptive fuzzy sliding mode controller for nonlinear systems

In this paper, the stability analysis of the GA-based adaptive fuzzy sliding model controller for a nonlinear system is presented. First, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via the reference model and the fuzzy model involving fuzzy logic control rules. Next, the difficulty in designing a fuzzy sliding mode controller (FSMC) capable of rapidly and efficiently controlling complex and nonlinear systems is how to select the most appropriate initial values for the parameter vector. The initial values of the consequent parameter vector are decided via the genetic algorithm. After this, a modified adaptive law can be adopted to find the best high-performance parameters for the fuzzy sliding model controller. The adaptive fuzzy sliding model controller is derived to simultaneously stabilize and control the system. The stability of the nonlinear system is ensured by the derivation of the stability criterion based upon Lyapunov’s direct method. Finally, a numerical simulation is provided as an example to demonstrate the control methodology.     

Fuzzy sliding mode control of a finger of a humanoid robot hand

Abstract: The motion control problem for the finger of a humanoid robot hand is investigated. First, the index finger of the human hand is dynamically modelled as a kinematic chain of cylindrical links. During construction of the model, special attention is given to determining bone dimensions and masses that are similar to the real human hand. After the kinematic and dynamic analysis of the model, in order to ensure that the finger model tracks its desired trajectory during a closing motion, a fuzzy sliding mode controller is applied to the finger model. In this controller, a fuzzy logic algorithm is used in order to tune the control gain of the sliding mode controller; thus, an adaptive controller is obtained. Finally, numerical results, which include a performance comparison of the proposed fuzzy sliding mode controller and a conventional sliding mode controller, are presented. The results demonstrate that the proposed control method can be used to perform the desired motion task for humanoid robot hands efficiently.     

不同维分数阶混沌预设时间有限时间投影同步

对于不同维分数阶混沌系统的投影同步问题,设计了一种自适应滑模控制器。这使得带有内部不确定量和外部扰动的驱动,响应系统能够在任意预设的时间完成同步,自适应律可以逼近未知量的上界。并针对自适应滑模控制器由于干扰产生抖振的问题,提出了两种解决方案。首先是设计二维滑模控制表,将模糊控制方法加入滑模控制器组成模糊自适应滑模控制器...     

无刷直流电机的自适应模糊滑模控制策略研究

为了提高无刷直流电机（BLDCM,brushless dC motor）控制系统的动态响应速度和干扰抑制能力,提出了一种新的自适应模糊滑模控制（AFSMC,adaptive fuzzy sliding mode control）策略。控制系统根据滑模开关函数的取值范围,可以切换滑模控制器的输出,能够改进滑模观测器的抖振现象和系统稳定性。控制器的控制律由自适应模糊控制算法调节,滑模控制器的输出减少了系统不确定时延的影响。根据所提出控制策略建立了仿真模型,并进行了仿真。仿真结果表明,所提出的控制策略能提高系统的动态性能和鲁棒性。该方法用于无刷直流电机的控制是可行的、有效的。     

Adaptive fuzzy controller with sliding surface for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate model for designing a model-based controller. Here, an adaptive fuzzy sliding mode controller is proposed to suppress the sprung mass position oscillation due to road surface variation. This intelligent control strategy combines an adaptive rule with fuzzy and sliding mode control algorithms. It has online learning ability to deal with the system time-varying and nonlinear uncertainty behaviors, and adjust the control rules parameters. Only eleven fuzzy rules are required for this active suspension system and these fuzzy control rules can be established and modified continuously by online learning. The experimental results show that this intelligent control algorithm effectively suppresses the oscillation amplitude of the sprung mass with respect to various road surface disturbances.     

An adaptive fuzzy sliding mode controller for robotic manipulators

This paper proposes an adaptive fuzzy sliding mode controller for robotic manipulators. An adaptive single-input single-output (SISO) fuzzy system is applied to calculate each element of the control gain vector in a sliding mode controller. The adaptive law is designed based on the Lyapunov method. Mathematical proof for the stability and the convergence of the system is presented. Various operation situations such as the set point control and the trajectory control are simulated. The simulation results demonstrate that the chattering and the steady state errors, which usually occur in the classical sliding mode control, are eliminated and satisfactory trajectory tracking is achieved.     

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.     

机器人操作器的自适应模糊滑模控制器设计

针对机器人动力学系统提出了一种基于模糊逻辑的自适应模糊滑模控制方案.根据滑模控制原理并利用模糊系统的逼近能力设计控制器,基于李雅谱诺夫方法设计自适应律,证明了闭环模糊控制系统的稳定性和跟踪误差的收敛性.控制结构简单,不需要复杂的运算.该设计方案柔化了控制信号,减轻了一般滑模控制的抖振现象.仿真结果表明了所提控制策略的有效性.