腰部外骨骼线性自抗扰控制研究

如今,物流搬运部分行业仍然严重依赖手动搬运.长期的搬运工作会极大地增加腰背肌肉劳损,甚至导致腰椎疾病.随着外骨骼系统的迅速发展,为搬运工开发腰部外骨骼至关重要.文中提出了一种线性扩张观测器的自抗扰控制算法.在搬运物体重量未知的情况下,该算法可以使得腰部外骨骼准确平滑地跟踪腰部运动轨迹.穿戴者搬运物体时,线性扩张观测器近...     

四辊卷板机侧辊位移线性自抗扰控制

侧辊位移的精确控制对实现四辊卷板机高效加工至关重要,其核心问题是提高阀控非对称缸电液伺服系统的抗扰能力。由于电液伺服系统具有高度非线性和时变不确定性,传统非线性控制方法很难有效处理包含未知动态、外部扰动以及参数变化等的多源不确定扰动。提出一种四辊卷板机侧辊位移线性自抗扰控制方法。综合考虑各种不确定扰动因素的影响,设计了线性扩张状态观测器进行实时估计,采用状态误差反馈控制律给予主动补偿,并消除跟踪误差,证明了线性扩张状态观测器状态观测误差的收敛性和电液伺服系统的闭环稳定性。试验结果表明,所设计的线性自抗扰控制器能有效抑制电液伺服系统中多源不确定性扰动,实现侧辊位移的快速、精确轨迹跟踪。     

阀控单出杆缸电液伺服系统二阶线性自抗扰控制

为提高阀控单出杆缸电液伺服系统性能,在构建阀控单出杆缸电液伺服系统动态机理模型基础上,提出了一种具有加速度前馈的二阶线性自抗扰控制(Linear Active Disturbance Rejection Control,LADRC)方法,采用奇异摄动理论分析了闭环系统稳定性,并针对系统响应性能和抗干扰性能与传统PID控...     

磁悬浮系统的积分滑模自抗扰控制

针对磁悬浮系统存在着非线性、时滞和易受到其它不确定性因素干扰的问题,首先建立了单自由度的磁悬浮系统模型,提出一种基于积分滑模自抗扰的位置控制算法。算法利用扩张状态观测器对悬浮球的位置和未知干扰进行估计,再将估计的位置信息和干扰项用于控制的反馈和控制量的补偿。将积分滑模控制引入到非线性状态误差反馈控制律中,设计了积分滑模自抗扰控制器,并根据Lyapunov理论对控制系统的稳定性进行了证明。仿真结果表明,所设计的积分滑模ADRC控制器实现了对磁悬浮球的位置控制,对系统存在的内外扰动和不确定性具有较强的鲁棒性,同时能对设定位置信息进行跟踪,并有较好的动态特性。     

航空相机前向像移补偿的线性自抗扰控制

为消除飞机姿态角速度变化对摆扫式航空相机反射镜组件进行前向像移补偿时的扰动,设计了线性自抗扰控制器(LADRC),研究了角速度扰动与力矩扰动的等效关系和扰动估计及补偿方法.首先,分析了飞机姿态角速度扰动对像移补偿的影响;然后,建立了有力矩扰动作用时反射镜系统的数学模型,设计了用于扰动观测与估计的线性扩张状态观测器及带扰...     

全向移动机器人的自抗扰轨迹跟踪控制

针对4-Mecanum轮全向移动机器人轨迹跟踪问题,设计了一种自抗扰控制器。首先对机器人的运动学与动力学模型进行分析;其次由反步法设计运动学控制器,并根据机器人在运动过程中受到未知干扰的现象,设计了改进的扩张状态观测器和动力学控制器;最后在不同扰动的作用下进行仿真。对比结果表明该控制器跟踪误差小,收敛速度快,观测器能够快速准确地估计出不确定因素对机器人的扰动并进行实时补偿,验证了该控制器具有较好的抗干扰性和鲁棒性。     

电液位置伺服系统自抗扰控制研究

由于电液位置伺服系统中存在不易获得精确数学模型、参数摄动以及外部未知扰动等问题,采用了一种改进自抗扰控制方案,充分利用系统已知信息,将系统位置误差作为控制器输入,以减小因扩张状态观测器产生的相位滞后,进而提高系统响应速度。同时对系统位置误差进行观测并予以补偿,并将系统高阶项以及未知扰动视为总扰动,以简化控制器结构,最后采用MATLAB与AMESim进行联合仿真。结果表明,所设计的一阶非线性自抗扰控制器能够实现系统的快速响应及精度控制,相较于改进前,响应速度提升47.62%,跟踪误差降低44.44%,与PID控制相比,响应速度提升了60%,跟踪误差降低了58.34%,对未知扰动等因素有良好的抑制能力,拥有更优良的控制品质和鲁棒性。     

基于死区补偿的电液位置伺服系统自抗扰控制

针对电液位置伺服控制系统的比例阀死区、参数不确定及外部未知扰动等问题,设计了由自抗扰控制器与死区逆补偿构成的串联控制器.首先基于实验辨识构造死区逆模型对死区进行预补偿,然后根据系统特性设计了一阶自抗扰控制器,构造改进的扩张状态观测器对"总扰动"进行实时估计,并通过非线性控制律给予主动补偿.联合仿真与试验结果表明,所提出...     

发电机组柴油机转速自抗扰控制的应用

为提升发电机组用发动机的抗干扰能力,增强其竞争优势,从发动机转速控制角度设计一种基于扩张状态观测器变结构自抗扰控制器,来满足发电机组非线性、时变的工作特性。通过试验验证其设计的自抗扰控制算法与传统PID控制算法对发动机转速的控制效果。试验结果表明:发动机转速自抗扰控制算法能够满足发电机组稳态及动态频率特性需求,相对传统控制在抗扰性能上有所提高,满足跟踪需求。     

电动机自抗扰控制技术研究综述

本文介绍了自抗扰控制技术在电机驱动中的应用,自抗扰控制技术解决了电机实时控制中具有不确定参数难以整定的问题,基于自抗扰控制器(ADRC)的原理,估计补偿电机控制中总的扰动项(包括内扰和外扰),提高了控制系统的鲁棒性和动态性能.     

Active disturbance rejection control based human gait tracking for lower extremity rehabilitation exoskeleton

This paper presents an active disturbance rejection control (ADRC) based strategy, which is applied to track the human gait trajectory for a lower limb rehabilitation exoskeleton. The desired human gait trajectory is derived from the Clinical Gait Analysis (CGA). In ADRC, the total external disturbance can be estimated by the extended state observer (ESO) and canceled by the designed control law. The observer bandwidth and the controller bandwidth are determined by the practical principles. We simulated the proposed methodology in MATLAB. The numerical simulation shows the tracking error comparison and the estimated errors of the extended state observer. Two experimental tests were carried out to prove the performance of the algorithm presented in this paper. The experiment results show that the proposed ADRC behaves a better performance than the regular proportional integral derivative (PID) controller. With the proposed ADRC, the rehabilitation system is capable of tracking the target gait more accurately.     

基于自抗扰重复控制的压电驱动器高精度跟踪控制

针对压电驱动器的高精度控制问题,提出一种自抗扰重复控制设计方法。首先,给出压电驱动系统的动力学模型;然后,在线性自抗扰控制(LADRC)中引入输出反馈积分控制器和一类插入式重复控制器,提出一种具有阶跃、斜坡和周期信号跟踪/抑制能力的自抗扰重复控制策略。进一步,结合小增益定理,分析闭环系统的稳定性及控制系统的设计方法。最后,将所提方法应用于一类压电驱动系统,实验结果表明该方法与LADRC相比,能显著提升控制效果,且高精度跟踪/抑制多种外部信号。     

Fractional active disturbance rejection control

A fractional active disturbance rejection control (FADRC) scheme is proposed to improve the performance of commensurate linear fractional order systems (FOS) and the robust analysis shows that the controller is also applicable to incommensurate linear FOS control. In FADRC, the traditional extended states observer (ESO) is generalized to a fractional order extended states observer (FESO) by using the fractional calculus, and the tracking differentiator plus nonlinear state error feedback are replaced by a fractional proportional-derivative controller. To simplify controller tuning, the linear bandwidth-parameterization method has been adopted. The impacts of the observer bandwidth ω_o and controller bandwidth ω_c on system performance are then analyzed. Finally, the FADRC stability and frequency-domain characteristics for linear single-input single-output FOS are analyzed. Simulation results by FADRC and ADRC on typical FOS are compared to demonstrate the superiority and effectiveness of the proposed scheme.     

基于 GA-模糊 RBF 的发电机组滑模自抗扰控制

针对燃煤发电机组风烟系统大惯性、大滞后、参数不稳定等特点,提出一种基于发电机组的滑模自抗扰控制策略。选择模糊径向基函数(RBF)算法辨识模型,以梯度下降法和遗传算法分别对神经网络权值进行粗调和细调,通过扩张状态观测器估计系统内外部扰动,将非线性状态误差反馈控制律与滑模控制策略相结合以克服系统惯性、滞后和扰动的问题,并设计Lyapunov函数验证控制系统稳定性。仿真结果表明,滑模自抗扰控制与串级比例-积分-微分(PID)控制、滑模控制和自抗扰控制相比,在模型适配的情况下,所设计的控制策略在38 s达到设定值,无超调量;当向系统施加20%的反向阶跃干扰时,系统调节时间为39.5 s,超调量为3.4%。在模型失配情况下的调节时间为43.2 s,无超调量;当向系统施加20%的反向阶跃干扰时,系统调节时间为46.4 s,超调量为3.87%。工程应用结果表明,一次风量控制偏差在±10 000 m³/h以内,相比串级PID控制策略波动范围降低21%,系统抗干扰能力和鲁棒性得到有效提升。     

Performance analysis of active disturbance rejection tracking control for a class of uncertain LTI systems

The paper considers the tracking problem for a class of uncertain linear time invariant (LTI) systems with both uncertain parameters and external disturbances. The active disturbance rejection tracking controller is designed and the resulting closed-loop system׳s characteristics are comprehensively studied. In the time-domain, it is proven that the output of closed-loop system can approach its ideal trajectory in the transient process against different kinds of uncertainties by tuning the bandwidth of extended state observer (ESO). In the frequency-domain, different kinds of parameters׳ influences on the phase margin and the crossover frequency of the resulting control system are illuminated. Finally, the effectiveness and robustness of the controller are verified through the actuator position control system with uncertain parameters and load disturbances in the simulations.     

Composite disturbance rejection control based on generalized extended state observer

Traditional extended state observer (ESO) design method does not focus on analysis of system reconstruction strategy. The prior information of the controlled system cannot be used for ESO implementation to improve the control accuracy. In this paper, composite disturbance rejection control strategy is proposed based on generalized ESO. First, the disturbance rejection performance of traditional ESO is analyzed to show the essence of the reconstruction strategy. Then, the system is reconstructed based on the equivalent disturbance model. The generalized ESO is proposed based on the reconstructed model, while convergence of the proposed ESO is analyzed along with the outer loop feedback controller. Simulation results on a second order mechanical system show that the proposed generalized ESO can deal with the external disturbance with known model successfully. Experiment of attitude tracking task on an aircraft is also carried out to show the effectiveness of the proposed method.     

大口径深空探测天线的抗风干扰伺服系统

为了改善风载荷干扰对深空探测天线跟踪精度和寿命的影响,设计了位置环线性自抗扰控制器.由于扰动观测器可以改善系统性能,本文基于电机动力学机理,将电流与速度的反馈与负载的影响作为总扰动的一部分,通过静态增益对前向通道的惯性环节进行近似,极大地降低了扩张状态观测器的阶次;采用在线估计和补偿策略,抑制了风载荷干扰对控制系统的不利影响;利用描述函数法分析了包含摩擦特性的非线性系统闭环特性,说明这种控制策略可以避免极限环的产生.最后,开展了数学仿真和现场试验.在一深空探测系统上的应用结果显示,提出的控制策略超调比原产品减少了34％,抗击阵风干扰能力提高了60％,跟踪精度提高显著.得到的结果表明设计的控制策略提高了系统抗风干扰的能力.     

An adaptive navigation method for a small unmanned aerial rotorcraft under complex environment

Focusing on low navigation performance of small unmanned aerial rotorcraft under complex environment, a composite navigation method combined with adaptive Kalman filtering and radial basis function neural network prediction method is proposed to improve navigation performance during GPS outages. When the GPS signal is available, an adaptive Kalman filter based on covariance scaling is introduced to deal with the process noise in real time. Meanwhile, a radial basis function neural network is trained on line to construct the projection among input (output of the inertial measurement unit, attitude and GPS losing time) and output (position error and velocity error). During GPS outages, the radial basis function neural network can provide high performance error estimation for position and velocity to improve state information. Finally, a land vehicle test and a flight test have confirmed that the proposed method can improve the navigation performance largely under complex environment.     

Modified reduced order observer based linear active disturbance rejection control for TITO systems

This paper proposes an observer based control approach for two input and two output (TITO) plant affected by the lumped disturbance which includes the undesirable effect of cross couplings, parametric uncertainties, and external disturbances. A modified reduced order extended state observer (ESO) based active disturbance rejection control (ADRC) is designed to estimate the lumped disturbance actively as an extended state and compensate its effect by adding it to the control. The decoupled mechanism has been used to determine the controller parameters, while the proposed control technique is applied to the TITO coupled plant without using decoupler to show its efficacy. Simulation results show that the proposed design is efficiently able to nullify the interactions within the loops in the multivariable process with better transient performance as compared to the existing proportional-integral-derivative (PID) control methods. An experimental application of two tanks multivariable level control system is investigated to present the validity of proposed scheme.