Disturbance observer-based fuzzy fault-tolerant control for high-speed trains with multiple disturbances

The fault-tolerant control problem is investigated for high-speed trains with actuator faults and multiple disturbances.Based on the novel train model resulting from the Takagi–Sugeno fuzzy theory, a sliding-mode fault-tolerant control strategy is proposed. The norm bounded disturbances which are composed of interactive forces among adjacent carriages and basis running resistances are rearranged by the fuzzy linearity technique. The modeled disturbances described as an exogenous system are compensated for by a disturbance observer. Moreover, a sliding mode surface is constructed, which can transform the stabilization problem of position and velocity into the stabilization problem of position errors and velocity errors, i.e., the tracking problem of position and velocity. Based on the parallel distributed compensation method and the disturbance observer, the fault-tolerant controller is solved. The Lyapunov theory is used to prove the stability of the closed-loop system. The feasibility and effectiveness of the proposed fault-tolerant control strategy are illustrated by simulation results.

AC-DC Fuzzy Linear Active Disturbance Rejection Control Strategy of Front Stage of Bidirectional Converter Based on V2G

Aiming at the problems of output voltage fluctuation and current total harmonic distortion(THD)in the front stage totem-pole bridgeless PFC of two-stage V2G(Vehicle to Grid)vehicle-mounted bi-directional converter,a fuzzy linear active disturbance rejection control strategy for V2G front-stage AC-DC power conversion system is proposed.Firstly,the topologicalworkingmode of the totem-pole bridgeless PFC is analyzed,and themathematical model is established.Combined with the system model and the linear active disturbance rejection theory,a double closed-loop controller is designed with the second-order linear active disturbance rejection control as the voltage outer loop and PI control as the current inner loop.The controller can realize self-adaptive tuning of the proportional gain coefficient of the active disturbance rejection controller through fuzzy reasoning and realize self-adaptive control.Simulation and experimental results show that this method can better solve the problems of slow system response and high total harmonic distortion rate of input current and effectively improve the system’s robustness.

Fuzzy Sliding Mode Active Disturbance Rejection Control of an Autonomous Underwater Vehicle-Manipulator System

In this paper, a fuzzy sliding mode active disturbance rejection control(FSMADRC) scheme is proposed for an autonomous underwater vehicle-manipulator system(AUVMS) with a two-link and three-joint manipulator. First, the AUVMS is separated into nine subsystems, and the combined effects of dynamic uncertainties, hydrodynamic force, unknown disturbances, and nonlinear coupling terms on each subsystem are lumped into a single total disturbance. Next, a linear extended state observer(LESO) is presented to estimate the total disturbance. Then, a sliding mode active disturbance rejection control(SMADRC) scheme is proposed to enhance the robustness of the control system. The stability of the SMADRC and the estimation errors of the LESO are analyzed. Because it is difficult to simultaneously adjust several parameters for a LESO-based SMADRC scheme, a fuzzy logic control(FLC) scheme is used to formulate the FSMADRC to determine the appropriate parameters adaptively for practical applications. Finally, two AUVMS tasks are illustrated to test the trajectory tracking performance of the closed-loop system and its ability to reject and attenuate the total disturbance. The simulation results show that the proposed FSMADRC scheme achieves better performance and consume less energy than conventional PID and FLC techniques.

Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the precondition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model. Key words One-wheel car model - Active suspension system - Single input rule modules fuzzy reasoning - Pneumatic actuator - Disturbance observer Document code A CLC number TH16

Pneumatic active suspension system for a one-wheel car model using fuzzy reasoning and a disturbance observer

This paper presents the construction of a pneumatic active suspension system for a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is composed of fuzzy and disturbance controls, and the active control force is constructed by actuating a pneumatic actuator. A phase lead-lag compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension improves much the vibration suppression of the car model.

Process disturbances monitoring and recognition of short-circuiting GMAW by fuzzy c-means system

An intelligent fuzzy c-means system for process monitoring and recognition of process disturbances during short- circuiting gas metal arc welding （GMAW） is introduced in this paper. The raw measured and statistically test data of probability density distribution （ PDD ） and class frequency distribution （ CFD ） of welding electrical parameters are further processed into a 7-dimensional array which is designed to describe various welding conditions, and is employed as input vector of the intelligent fuzzy c-means system. The fuzzy c-means system is used to conduct process monitoring and automatic recognition. The correct recognition rate of 24 test data under 8 kinds of welding condition is 92%.

Fuzzy Adaptive Tracking Control of Uncertain Strict-Feedback Nonlinear Systems with Disturbances Based on Generalized Fuzzy Hyperbolic Model

In this paper, a fuzzy adaptive tracking control for uncertain strict-feedback nonlinear systems with unknown bounded disturbances is proposed. The generalized fuzzy hyperbolic model (GFHM) with better approximation performance is used to approximate the unknown nonlinear function in the system. The dynamic surface control (DSC) is used to design the controller, which not only avoids the “explosion of complexity” problem in the process of repeated derivation, but also makes the control system simpler in structure and lower in computational cost because only one adaptive law is designed in the controller design process. Through the Lyapunov stability analysis, all signals in the closed loop system designed in this paper are semi-globally uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the method is verified by a simulation example.

超高压应力增塑成形装备液压系统设计与控制

针对超高压应力增塑成形技术对压力和位置控制精度的需求,设计了一种超高压应力增塑成形装备液压系统,建立了液压系统的泵控缸数学模型和AMESim机电液仿真模型,针对液压缸速度波动较大以及压力控制效果较差的问题分别引入了模糊PID控制和三阶自抗扰控制策略。通过AMESim与Simulink的联合仿真验证了两种控制策略的有效性。仿真结果表明:模糊PID控制器对梯形速度曲线具有良好的跟踪效果,液压缸速度跟踪误差小于0.0035 m·s^(-1),明显消除了液压缸速度波动;自抗扰控制器提高了压力控制精度,压力曲线追踪阶段的压力误差小于0.05 MPa。整个系统的动态调节能力增强,位置和压力控制精度明显提升。

四旋翼无人机改进自抗扰姿态控制

针对四旋翼无人机姿态控制过程中模型不确定及外部扰动问题,设计了一种自抗扰控制的姿态控制器。将模糊控制方法与传统的自抗扰控制理论相结合,增加了一个集模糊化、模糊推理和清晰化为一体的模糊控制单元,采用改进天牛须算法整定自抗扰控制器参数,提高了参数整定效率。为解决fal函数拐点处不平滑,易产生小幅抖振以及误差较大时系统增益较大等问题,引入了改进的yfal函数替代扩张状态观测器中的fal函数,并对改进后的状态观测器进行了收敛性判断。仿真结果表明,改进后的自抗扰控制器具有更快的响应速度和抗干扰能力。

基于神经网络的微电网交错并联变换器的改进自抗扰控制

针对混合储能微电网在负载突变、扰动加入等多种复杂工况下引起的用电端降压接口的电压质量降低的问题,文章设计了一种以改进线性自抗扰为主要控制器,以BP神经网络为辅助参数优化算法的闭环控制策略。首先,根据六路交错并联变换器的电路拓扑建立时域下的数学模型,并对系统总扰动进行重构,将总扰动分解为模型未知扰动和外界扰动,分别利用观测器进行估计,形成了改进线性自抗扰控制,提高系统的扰动观测能力和观测精度;其次,为使系统获得控制参数的实时优化能力,引入BP神经网络,对控制器参数进行实时整定;最后,搭建了混合微电网六路交错并联变换器的数字仿真模型和半实物仿真模型进行验证,并与PI,LADRC进行了比较。结果显示,所提控制策略不仅具备优异的输出电压质量,而且使系统获得了更好的稳定性与鲁棒性。

考虑复杂扰动的轻型商用车路径跟踪混合控制方法

外界扰动、模型不确定性和参数摄动等复杂扰动直接影响智能车辆路径跟踪控制的精度和行驶安全性。商用车的载重特性使其在行驶过程中受到的复杂扰动更为明显,为提升自动驾驶商用车路径跟踪精度和平顺性,提出一种路径跟踪混合控制方法。首先,建立鲁棒性强的基于扩张观测器的滑模控制器和变化平稳的增量式LQR控制器,其中增量式LQR的参数使用粒子群算法整定。然后,使用模糊控制器将两者相结合,根据车速和横向误差调整权重系数,在提升系统鲁棒性的同时削弱抖振。最后,进行了仿真分析和实车试验。试验数据表明,SMC+LQR具备较好的控制效果,能应对外界的复杂扰动。

风扰下变质量四旋翼轨迹跟踪控制

针对存在风扰和变质量负载扰动的四旋翼无人机轨迹跟踪控制问题,提出了一种基于降阶广义比例积分观测器的动态面模糊滑模控制方法。首先,建立含风扰和变质量负载扰动的四旋翼无人机系统模型;其次,结合四旋翼无人机系统模型设计降阶广义比例积分观测器估计外界风扰;再次,设计动态面滑模控制器,并采用模糊控制模糊化切换增益,以此有效地抑制抖振;然后,通过Lyapunov稳定性证明四旋翼无人机系统的稳定性;最后,通过Matlab-Simulink进行3种控制方法的仿真比较。仿真结果表明,当存在风扰和变质量负载扰动时,该控制方法抗风扰能力更强,稳定性更好,位姿跟踪精度更高。

基于扩张状态观测器的伺服加载模糊滑模控制

针对电动伺服加载测试台存在的间隙、摩擦等非线性控制问题,以滑模变结构控制(SMC)为主体进行了加载控制器设计。分析伺服加载测试台整体结构,提出一种基于扩张状态扰动观测器(ESO)的模糊滑模控制(FSMC)策略。该策略在使用ESO针对伺服加载系统的外部干扰进行观测的基础上,设计了模糊控制对滑动模态面和滑模趋近律进行自适应调节,提高了系统的动态实时跟随能力和干扰补偿能力,并减小SMC控制器稳定时的抖振现象。仿真结果表明:所设计的基于扩张状态观测器的模糊滑模控制器(FSMC-ESO)对比传统SMC及PID控制具有更好的快速响应性和鲁棒性。

柔性多关节移动机器人非线性控制轨迹的二次模糊逼近

针对柔性多关节移动机器人在非线性控制轨迹下控制精准度不高的问题,提出一种非线性控制下的模糊逼近方法。建立机器人动力学模型,根据动力学特性设置矢量参数,对误差扰动动态修正。将矢量参数作为初始输入值,采用加权平均和乘积推理法,使得矢量符合自适应规律,通过模糊逼近函数对控制器的输出值实行状态逼近,直至符合初始设定值;凭借李亚普诺夫函数对控制输出值二次实施稳定模糊逼近,完成非线性轨迹控制。以B样条曲线轨迹为例做控制实验,实验数据证明:该二次逼近控制方法在非线性轨迹下的控制精准度较高,控制器输出力矩稳定,实用性能较强。

采用干扰补偿模糊整定的双柔性机械臂抑振策略

双柔性机械臂由柔性关节和变长度的柔性负载组成,会同时受到柔性、摩擦和参数时变的影响,在运动过程中,它会出现振动的现象,导致末端执行器的跟踪精度降低。本文采用基于干扰观测器的模糊整定PI策略控制双柔性机械臂伺服系统的输出转速,通过控制柔性负载的转速波动间接抑制机械臂的振动。根据假设模态法和拉格朗日原理建立了考虑变形的双柔性机械臂伺服系统的动力学方程。根据鲁棒稳定性理论设计干扰观测器中的低通滤波器,使干扰观测器同时满足控制器参数时变和受控对象参数摄动的稳定性。通过数值仿真分析和双柔性机械臂伺服系统控制实验,验证了所提方法的有效性。实验结果表明,本文提出的控制策略可以更好地消除参数时变和柔性对于输出转速的影响,提高末端执行器的控制精度。

直流伺服电机新型位置-速度控制策略

针对由直流电机位置伺服系统自身参数不确定以及外部扰动影响,导致系统响应速度、控制精度降低的问题,提出了一种新型位置-速度双环控制策略。速度控制器采用模糊内模PID(proportional-integral-differential)控制,利用模糊原理实现对内模PID控制器参数,即滤波时间常数λ的在线智能整定;位置控制器采用基于自抗扰的非奇异快速终端滑模控制(non-singular fast terminal sliding mode control,NFTSMC),利用线性扩张状态观测器对系统总体的内外干扰进行估计,并以反馈形式进行补偿,同时采用NFTSMC对系统的状态变量进行跟踪,以提高系统的跟踪性能和抗干扰性;最后使用仿真与实验方法验证了新型双闭环控制策略对直流电机位置伺服系统具有良好的控制性能。

模糊自抗扰优化开关磁阻电机速度环控制策略

开关磁阻电机因其结构为双凸极造成转矩脉动过大,且该系统具有严重的非线性,给定转速变化大,负荷扰动大,为克服这个问题应用模糊自抗扰控制方法,结合开关磁阻电机特性和机械运动方程,建立开关磁阻电机双闭环系统仿真模型,转速环采用自抗扰控制技术并使用模糊控制对其参数实施整定,转矩环采用直接瞬时转矩控制,仿真对比得出,相较于传统PI控制,模糊自抗扰控制能够有效改善调速性能,降低转矩脉动,表现出良好的抗干扰能力。

一种克服大范围随机扰动的全信息FUZZY控制器

通过对FUZZY控制器的分析,给出了一种新型的全信息FUZZY控制器,解决了影响FUZZY控制器控制精度的问题即系统信息丢失问题。该FUZZY控制器的设计方法较传统的FUZZY控制器简单。仿真结果表明,用该方法设计的FUZZY控制器对大范围随机扰动克服效果较好。

跷跷板系统干扰补偿的分层滑模控制策略研究

为提高跷跷板系统在外部干扰下的平衡控制性能,提出一种基于指数收敛干扰观测器与切换增益模糊自适应分层滑模控制相结合的复合控制策略。首先,设计一种指数收敛干扰观测器,对系统受到的外部扰动等不确定因素进行估计补偿,以改善控制器鲁棒性。该观测器不需要状态变量二阶导的信息,可以应对实际工程中难以通过求导的方式获取加速度信号的问题。然后,针对跷跷板这类强耦合欠驱动系统提出一种分层滑模控制算法,并进一步针对滑模控制算法在未知大干扰下切换增益过大的问题,通过模糊规则的设计将切换增益模糊化,以降低系统抖振。最后,仿真和试验结果表明,相较于传统的滑模控制算法,该分层滑模控制算法抗干扰能力更强、切换增益更低。该策略可应用于类跷跷板平衡控制的实际系统。

基于改进模糊滑模控制的列车速度跟踪研究

列车运行过程具有强耦合、非线性等特征,且往往存在较大且不可观测的外界干扰,这些特性加大了列车运行控制的难度,针对列车运行速度跟踪控制问题,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,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;然后构造以李亚普洛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,并且引入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,且有效地消除了控制器的抖振情况;最后通过仿真算例验证了所提方法的有效性,且提高了列车运行控制系统性能。