Design of active disturbance rejection internal model control strategy for SISO system with time delay process

A novel control scheme of active disturbance rejection internal model control(ADRIMC) is proposed to improve the anti-interference ability and robustness for the dead-time process. The active anti-interference concept is introduced into the internal model control(IMC) by analyzing the relationship between IMC and disturbance observer control(DOB). Further, a design process of disturbance filter is presented to realize the active anti-interference ability for ADRIMC scheme. The disturbance filter is used to estimate an equivalent disturbance consisting of both external disturbances and internal disturbances caused by model mismatches.Simulation results demonstrate that the proposed method possesses a good disturbance rejection performance, though losing some partial dynamic performance. In other words, the proposed method shows a tradeoff between the dynamic performance and the system robust.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Multi-loop Internal Model Controller Design Based on a Dynamic PLS Framework

In this paper,a multi-loop internal model control(IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares(DyPLS) framework is proposed.Unlike the traditional methods to decouple multi-input multi-output(MIMO) systems,the DyPLS framework automatically decomposes the MIMO process into a multi-loop system in the PLS subspace in the modeling stage.The dynamic filters with identical structure are used to build the dynamic PLS model,which retains the orthogonality among the latent variables.To address the model mismatch problem,an off-line least squares method is applied to obtain a set of optimal filter parameters in each latent space.Without losing the merits of model-based control,a simple and easy-tuned IMC structure is readily carried over to the dynamic PLS control framework.In addition,by projecting the measurable disturbance into the latent subspace,a multi-loop feed-forward control is yielded to achieve better performance for disturbance rejection.Simulation results of a distillation column are used to further demonstrate this new strategy outperforms conventional control schemes in servo behavior and disturbance rejection.

Control Design for Harmonic Disturbance Rejection for Robot Manipulators with Bounded Inputs

Currently most of control methods are of one degree of freedom（1-DOF） control structure for the robot systems which are affected by unmeasurable harmonic disturbances,at the same time in order to obtain perfect disturbance attenuation level,the controller gain must be increased.In practice,however,for robotic actuators,there are physical constraints that limit the amplitude of the available torques.This paper considers the problem of tracking control under input constraints for robot manipulators which are affected by unmeasurable harmonic disturbances.A new control scheme is proposed for the problem,which is composed of a parameter-dependent nonlinear observer and a tracking controller.The parameter-dependent nonlinear observer,designed based on the internal model principle,can achieve an estimation and compensation of a class of harmonic disturbances with unknown frequencies.The tracking controller,designed via adaptive control techniques,can make the systems asymptotically track the desired trajectories.In the control design,the continuous piecewise differentiable increasing function is used to limit control input amplitude,such that the control input saturation is avoided.The Lyapunov stability of closed loop systems is analyzed.To validate proposed control scheme,simulation results are provided for a two link horizontal robot manipulator.The simulation results show that the proposed control scheme ensures asymptotic tracking in presence of an uncertain external disturbance acting on the system.An important feature of the methodology consists of the fact that the designed controller is of 2-DOF control structure,namely,it has the ability to overcome the conflict between controller gain and robustness against external disturbances in the traditional 1 -DOF control structure framework.

Application of improved active disturbance rejection control algorithm in tilt quad rotor

The Tilt Quad Rotor(TQR) has complex dynamics characteristics, especially in conversion mode. It is difficult to build the dynamic model of the TQR and the environmental factors have a great influence on it. To solve the problem of control in conversion mode of TQR, this paper carries out the design of the controller based on improved Active Disturbance Rejection Control(ADRC). According to the characteristics of flight in conversion mode, Tracking Differentiator(TD) with explicit model is used to solve the problem of multiple integrals when the system is high-order system. Extended State Observer(ESO) with Radial Basis Function(RBF) neural network is used to estimate and compensate for internal and external uncertainties, and the adaptive sliding mode control in Nonlinear State Error Feedback(NLSEF) is used to improve the response speed of the controller and reduce the parameters which should be tuned. Through the flight control simulation of the TQR, the validity and rationality of the control system are verified.

Robust PID controller design for time delay processes with peak of maximum sensitivity criteria

The motivation of this work is to obtain single PI/PID tuning formula for different types of processes with enhanced disturbance rejection performance. The proposed tuning formula consistently gives better performance in comparison to several well-known methods at the same degree of robustness for stable, integrating and unstable processes. For the selection of the closed-loop time constant(τc), a guideline is provided over a broad range of time-delay/time-constant ratios on the basis of the peak of maximum sensitivity(Ms). An analysis has been performed for the uncertainty margin with the different process parameters for the robust controller design. It gives the guideline of the Ms-value settings for the PI controller designs based on the process parameters uncertainty. Furthermore, a relationship has been developed between Ms-value and uncertainty margin with the different process parameters(k, τ and θ). Simulation study has been conducted for the broad class of processes and the controllers are tuned to have the same degree of robustness by measuring the maximum sensitivity, Ms, in order to obtain a reasonable comparison.

模型信息联合校正型自抗扰控制策略

为解决微电网受到不确定扰动时,会对直-直变换器输出的电能质量产生严重影响的问题,该文提出一种模型信息联合校正型自抗扰控制技术(ADRC-MIR)。在该控制策略中,首先借助串联超前校正的思想,以比例微分校正环节对线性扩张状态观测器的扰动观测传递函数进行修正,使其可实现对总和扰动更精确的跟踪;然后,根据状态空间平均法从被控系统中提取部分模型信息,将其写入修正后的线性扩张状态观测器的系数矩阵并最终构建出ADRC-MIR;随后基于理论推导,给出改进控制器的参数整定公式及其物理意义,并从噪声抑制、扰动抑制及其频域特性等方面指出改进后的控制器可提升控制品质的原因。最后通过对比不同工况下的数值仿真验证所提控制策略的可行性与正确性。

直线型倾转多旋翼植保无人机建模与控制

针对直线型倾转多旋翼植保无人机模型耦合复杂、作业时易受施药执行器干扰等问题,提出了一种模型补偿-线性自抗扰控制算法。首先建立无人机运动学和动力学模型,并分析作业时离心喷头产生的力矩作用影响;然后将作业模型中的固定部分作为已知扰动,引入模型补偿-扩张状态观测器估计内外未知总扰动并动态补偿控制系统,完成位姿控制器设计。仿真结果表明,所提出的算法在作业场景下偏航角度误差小于0.2°,恢复时间小于0.55 s,相比于PID算法和线性自抗扰算法最大角度偏差分别降低3.4°和0.9°,恢复时间减少3.1和0.99 s,具有较强的鲁棒性。飞行实验表明,该无人机可以很好地跟踪植保作业轨迹,最大位置稳态误差小于15 cm,满足植保作业需求。

刚性联接双电机系统功率平衡控制策略

针对刚性联接双电机系统因参数摄动和负载变化导致的系统输出功率不均衡问题,基于转矩闭环矢量控制系统,提出了一种自抗扰模型预测(ADRC-MPCC)转矩交叉耦合功率平衡控制策略。首先,建立刚性联接双电机系统的统一数学模型,基于该模型分析了功率不平衡产生的原因;其次,通过确定合适的转矩反馈补偿系数,提高了系统中双电机的同步性能;最后,设计自抗扰控制器对转速环、磁链环和转矩环的扰动进行估计和补偿,并通过简化模型预测控制方法对逆变器开关状态进行选择,减少了控制器的运算时间。仿真与实验结果表明,提出的控制策略实现了参数摄动和负载扰动情况下刚性联接双电机系统的输出功率平衡,验证了功率平衡控制策略的有效性。

基于改进型ADRC的PMSM无位置传感器控制

针对永磁同步电机矢量控制中传统速度环PI调节器存在协调性与抗干扰能力差的问题,引入自抗扰控制(ADRC)替代速度环PI调节器,考虑到线性ADRC中PD控制存在性能较差的缺点,选择滑模控制代替PD控制,提出改进型ADRC控制方法;同时采用模型参考自适应系统(MRAS)取代传统机械式位置传感器对电机的转子位置进行检测,实现了永磁同步电机无位置传感器控制。通过采用改进型ADRC与MRAS相结合的控制方法,电机控制系统具有了更好的动态响应速度和抗干扰能力。最后通过永磁同步电机对拖实验平台对电机在转速恒定负载突变和带载启动转速突变两种工况下进行实验,验证了改进型ADRC与MRAS相结合的控制策略的有效性。

基于联合仿真的电励磁同步电机线性自抗扰控制

针对电励磁同步电机(EESM)在车用电机控制方向的研究,通过Maxwell设计EESM有限元模型,基于Simulink搭建电机控制系统模型。然后,根据凸极EESM的电机特性和电磁转矩分析,在控制系统中采用最大转矩电流比(MTPA)矢量控制方式在Simulink-Maxwell进行EESM控制系统的联合仿真验证。同时,控制系统电流环应用线性自抗扰控制(LADRC),基于电机已知参数在LADRC中设计模型辅助—扩张状态观测器(MA-LESO),以观测和消除系统扰动变量。仿真实验表明,采用MTPA矢量控制的电机在带载时转速波动降低,带载能力增强;在电流环中采用MA-LESO的LADRC控制器能使电机转速在稳态时波动更小,在带载时的抗干扰性能更强,电机运行过程相对稳定;电机负载转矩和定子电流在空载、负载时的波形更稳定,显著提升了电机运行性能。

基于混合深度学习的压气机喘振快速诊断及自抗扰控制方法

[目的]为了提升压气机设备安全、稳定运行的水平,提出一种基于混合深度学习参数辨识的喘振状态快速诊断方法,以及一种用于实现压气机退喘的自抗扰控制策略。[方法]首先,采用长短期记忆神经网络(LSTM)处理压气机参数辨识输入输出数据的时序关系,并融入高斯过程回归(GPR)的区间概率估计能力,提出一种基于LSTM和GPR结合(LSTM-GPR)的混合深度学习参数辨识算法,进而实现对压气机喘振状态的快速诊断;然后,基于自抗扰控制方法对压气机的节流阀参数进行控制,通过控制量对压气机节流阀参数的补偿,实现对压气机喘振状态的准确控制。[结果]结果表明,混合深度学习参数辨识算法可以实现对压气机临界Greitzer参数的准确辨识,能快速、准确地判断出压气机是否处于喘振状态,并且基于自抗扰控制的控制策略,可以使压气机有效退出喘振状态,相比传统的PID控制和非线性反馈控制等控制方法,所提方法快速、有效,可保证压气机的工作范围。[结论]提出的参数辨识和自抗扰控制方法能够用于压气机的喘振诊断和主动控制,可提升压气机的安全性与稳定性。

模型预测转矩自抗扰控制下直驱永磁同步发电机最大追踪系统

为了更好地获取风能,构建了一种基于模型预测转矩自抗扰的最大功率追踪控制系统,用于直驱永磁同步发电机(permanent magnet synchronous generator,PMSG)来实现系统的最大输出功率追踪。为了提升PMSG响应性能,增强PMSG抗扰动性能,首先在电流环设计了模型预测转矩控制(model predictive torque control,MPTC),同时在速度环提出了一种参数补偿改进自抗扰控制(active disturbance rejection control,ADRC)策略,该方法继承了ADRC和MPTC的优点,可以很好地处理内部和外部干扰、建模误差和风速变化等不确定性问题,以实现在不同风速下最大功率追踪性能。从仿真结果可知当风速变化较小时所提控制策略转速静态误差几乎为0,传统MPTC控制策略误差为0.2 rad/s;当风速变化较大时所提控制策略转速静态误差较小,传统MPTC控制策略误差达到5 rad/s。研究结果表明所提出的控制方法在最大功率追踪较传统控制器具有更好的动态响应性能以及抗干扰性能。

双重化PWM整流器自抗扰模型预测直接功率控制

针对车载双重化脉宽调制(pulse width modulation,PWM)整流器控制性能易受到模型不确定性和列车运行条件(输入电压、功率等级、电路参数等)变化影响的问题,提出一种基于自抗扰控制(active disturbance rejection control,ADRC)和模型预测直接功率控制(model predictive direct power control,MPDPC)的双闭环控制算法。其中,外环基于自抗扰控制理论,构建了基于误差驱动的ADRC(error-based ADRC,EADRC)控制器调节直流侧电压;内环结合基于内模原理的功率补偿方案使用两步MPDPC算法实现电流信号的控制。仿真和实验将所提自抗扰模型预测直接功率控制(ADRC-MPDPC)算法与传统基于比例积分的直接功率控制(proportional integral-based direct power control,PI-DPC)算法和PI-MPDPC方法进行对比,结果表明所提策略在系统启动、负载变化及工况切换等场景表现出更优的动态特性和鲁棒性能。

电液位置伺服系统低阶自抗扰控制研究

电液位置伺服系统是一种时变非线性、外部扰动未知且数学模型复杂的高阶系统,对其采用的高阶自抗扰控制方法,需要整定参数较多,模型结构复杂,在实际工程应用中难以实现。针对这个问题,对电液位置伺服系统的一阶和二阶自抗扰控制(ADRC)性能进行研究,实现电液位置伺服系统的低阶自抗扰控制。基于Simulink建立的电液位置伺服系统的低阶自抗扰控制系统,给定阶跃和正弦信号指令,并对系统施加一个负载扰动力,分析系统的响应速度、准确性和抗干扰能力。结果表明,一阶和二阶自抗扰控制都可以使电液位置伺服系统达到稳定状态,且二阶非线性自抗扰控制系统响应速度更快,控制精度高,鲁棒性更强。

基于延迟补偿的永磁同步电机并行自抗扰控制

为了解决永磁同步电机在多工况下转速易受到内外扰动的影响,提出一种基于延迟补偿的并行线性自抗扰控制策略。针对永磁同步电机可能受到信号处理、逆变器响应等因素从而引入的外部时滞效应的问题,引入Smith预估器与自抗扰控制相结合,使控制系统更加精确、快速地响应内部参数变化和外部扰动。同时,针对线性自抗扰控制器(LADRC)在有限带宽内其抗扰性能较差的问题,设计了并行线性自抗扰控制器,在保持其带宽不变与参数易于整定的同时,有效提高其抗扰动能力。最后,对自抗扰控制器的稳定性进行了分析,并在此基础上进行了参数设计与扰动性能分析。仿真与实验结果表明,所提算法相比LADRC在电机受到速度阶跃、负载扰动与内部参数变化时,在调整时间上分别提升了52.5%、49.5%与42.4%,从而验证了该控制策略能有效增强永磁同步电机在多工况下抗内外扰动与速度跟踪能力。

重型液压机械臂的模型前馈补偿自抗扰控制

液压驱动的重型机械臂被广泛应用于工程机械和矿山机械,对其进行自动控制在行业内具有迫切的需求。然而,液压系统的强参数不确定性和难以建模的动态等因素的影响,给其自动控制带来了一定的挑战。文中以某锚杆钻车为例,研究了一类重型液压机械臂驱动液压缸的位置跟踪控制问题,提出了一种模型前馈补偿自抗扰控制器。为解决重载下变负荷、死区、参数不确定以及摩擦等非线性因素带来的控制难题,采取模型前馈与自抗扰反馈相结合的控制方法,将重型液压机械臂的机构动力学模型和比例阀控液压缸模型相结合,建立了系统的机理模型,然后基于系统的机理模型,构建了控制器的前馈补偿部分;设计了扩张状态观测器对系统的未建模因素进行实时观测,再加上基于状态误差的反馈调整构成了自抗扰控制器。最后在实际的重型液压机械臂上进行了实验研究,结果表明:基于模型前馈补偿的自抗扰控制器相比于PID控制器,具有更小的滞后和跟踪误差,整体跟踪精度比PID控制器提升了63.5%,说明所设计的控制器可以很好地克服液压系统的非线性因素的不利影响,比PID控制器具有更高的鲁棒性,因此所设计的控制方法更适用于此类重型液压机械臂的位置跟踪控制。

基于无模型的PMLSM改进自适应滑模自抗扰控制

为了提高永磁直线同步电机的自抗扰控制的动态响应性能和抗干扰性能,增强系统整体的控制性能,提出了一种基于无模型控制的改进滑模自抗扰控制策略。首先,基于滑模变结构原理以及无模型控制理论对自抗扰控制器中的扩张状态观测器和非线性状态误差反馈进行优化,建立了超局部模型,采用非奇异快速终端滑模控制代替原有的非线性状态误差反馈,同时设计相应滑模面与扩张状态观测器相结合,提高观测器对扰动因素的观测精确度的同时增强控制器的动态响应性能和抗干扰能力。然后设计了改进指数趋近率,通过引入系统状态变量使得控制器可以进行自适应调节,进一步提高系统的控制性能。通过李雅普诺夫理论证明了控制策略的稳定性,仿真和实验结果表明,该控制策略相对传统的自抗扰控制器所具备的优越性。

光电稳定平台的模型修正自抗扰控制

针对光电稳定平台易受摩擦力、载体运动姿态变化等扰动影响导致稳定精度降低的问题,提出一种模型修正自抗扰控制方法。根据系统辨识获得的光电稳定平台模型参数信息,设计模型扩张状态观测器准确估计系统各阶状态变量,在控制律中对总扰动进行补偿,将被控对象模型改造成准确的辨识模型形式,并基于该辨识模型设计误差反馈控制器,实现对光电稳定平台的稳定控制。实验结果表明,所提方法在低速跟踪正弦信号的实验中表现出更好的跟踪性能;对于载体运动带来的速度扰动,模型修正自抗扰控制方法的稳定精度有了明显提升。从而验证了本文方法在光电稳定平台速度跟踪和扰动抑制方面的良好性能。

基于模型参考自适应自抗扰的风电系统最大功率控制

为实现直驱永磁同步发电机(permanent magnet synchronous generator,PMSG)的最大输出功率追踪,构建了一种基于模型参考自适应自抗扰控制的永磁同步风力发电系统最大功率控制系统。首先,搭建模型参考自适应系统(model reference adaptive system,MRAS)来估算风力发电系统的角速度,实现控制系统的无位置控制,并对MRAS中的PI反馈自适应无法快速跟踪转速且具有超调等问题,提出伪微分反馈自适应率,有效提升无位置控制的精度;同时,为提高PMSG动态响应性能,增强PMSG的抗干扰性能,增强出速度环自抗扰控制(active disturbance rejection control,ADRC)策略,可以很好地进行风速跟踪,确保在不同风速下实现最大功率追踪。仿真结果表明,当风速变化较小时所提控制策略转速估计误差很小,而传统MRAS控制策略初始位置估计误差超过了10 rad/s,同时动态过程中也存在一定的跟踪误差,当风速变化剧烈时所提控制策略转速跟踪误差不是很大,而传统MRAS控制策略误差超过10 rad/s。研究结果表明,所提控制策略可以准确地追踪转速,并具有较好的动态性能。