Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Combined disturbance-observer-based control and iterative learning control design for pulsed superconducting radio frequency cavities

The development of iterative learning control combined with disturbance-observer-based(DOB)control for the digital low-level radio frequency(LLRF)system of the International Linear Collider project is presented.The objective of this study is to compensate for both repetitive(or predictable)and unpredictable disturbances in a radio frequency system(e.g.,beam loading,Lorentz force detuning,and microphonics).The DOB control approach was verified using the LLRF system at the Superconducting Test Facility(STF)at KEK in the absence of a beam.The method comprising DOB control combined with an iterative learning control algorithm was then demonstrated in a cavity-simulator-based test bench,where a simulated beam was available.The results showed that the performance of the LLRF system was improved,as expected by this combined control approach.We plan to further generalize this approach to LLRF systems at the STF and the future International Linear Collider project.

Observer design for matrix second order linear systems with uncertain disturbance input-a parametric approach

A simple parametric approach to design a full-order observer for matrix second-order linear systems with uncertain disturbance input in the matrixsecond-order framework is proposed. The basic idea is to minimize the H2 norm of the transfer function from disturbance to estimation error using the design degrees of freedom provided by a parametric approach in the observer design. Besides the design parameters, the eigenvalues of the closed-loop system are also optimized within desired regions on the left-half of the complex plane. Using the proposed approach, additional specifications can be easily achieved. A spring-mass system is using to show the effect of the proposed approaches.

未知扰动下的无人艇编队优化轨迹跟踪控制

[目的]针对水面无人艇(USV)编队轨迹跟踪中存在的未知扰动和队形变化问题,提出一种基于有限时间扰动观测器的最优反步控制(FDO-OBC)方法。[方法]首先,基于虚拟结构法,建立无人艇编队控制框架,并设计运动学和动力学编队控制器;其次,设计有限时间扰动观测器,实时估计补偿未知环境扰动;然后,针对编队队形变化的轨迹跟踪问题,提出基于最优反步控制的动态轨迹优化策略,利用扰动观测器信息来计算最优控制输入,实现无人艇编队轨迹跟踪的动态优化;最后,采用李雅普诺夫稳定性理论证明该编队控制方法的稳定性。[结果]仿真对比结果表明,FDO-OBC策略可有效提高无人艇编队系统的精确性和鲁棒性。[结论]对于面向扰动环境下的无人艇编队控制系统设计,FDO-OBC方法提供了一种新的技术手段。

电磁悬浮系统的改进线性自抗扰控制方法

单点电磁悬浮系统是常导电磁磁浮列车悬浮系统的关键控制单元。针对单点电磁悬浮系统因强干扰影响导致控制性能下降的问题,提出了一种改进型线性自抗扰控制(LADRC)方法。首先,基于电磁悬浮结构及原理建立了单点悬浮系统线性化模型,并对系统稳定性进行了分析。其次,基于自抗扰控制方法设计位置外环控制器以及基于PI调节器的电流内环控制器,对线性扩张状态观测器进行改进,设计两级级联的线性扩张状态观测器提高扰动估计精确度及速度,进而提高LADRC中扩张状态观测器对系统扰动的估计能力,并在频域上分析了改进型LADRC扰动估计性能和抑制能力的优越性。最后,搭建实验环境,对改进线性自抗扰控制方法的有效性进行验证。实验结果表明,所提的改进型LADRC不仅具有良好的位置跟踪性能,同时相比传统LADRC具有更强的抗扰动能力。

基于NESO-LFDC的四旋翼无人机滑模姿态控制

针对四旋翼无人机姿态控制中存在空气动力学特性复杂,易受干扰的特性,提出一种基于非线性扩张状态观测器(nonlinear extended state observer,NESO)和低频干扰补偿器(low-frequency disturbance compensator,LFDC)的非奇异快速终端滑模控制方法。该方法内环设计了NESO和LFDC结合,以获得干扰补偿值并补偿总干扰的低频分量。在外环设计了跟踪微分器和可变切换增益的非奇异快速终端滑模控制器,用于补偿虚拟干扰估计值的误差和总干扰的高频分量。仿真结果表明,该控制方法可以更好地估计总干扰的低频和高频分量,减少虚拟干扰估计值的误差对四旋翼无人机姿态控制的影响,并提升响应速度。

复合干扰作用下基于干扰观测器的系统运行优化控制

为了优化实际工业系统性能,降低损耗,针对不同类型干扰同时作用的系统,提出一种改进的两层运行优化控制算法来解决干扰对控制系统带来的影响。首先,采取传统两层运行优化控制框架结构,在底层设计PID控制器来保证控制系统的跟踪性能,使得系统的输出能尽可能地跟踪设定值;其次,根据作用于系统的复合噪声类型,结合H_(∞)方法在上层设计干扰观测器以及补偿控制器进行干扰抑制,以使系统的输出能够跟踪最优设定值;最后,通过数值仿真验证该方法的有效性。

新型永磁同步电机有限控制集无模型预测电流控制

为了减小永磁同步电机在启动时转速容易出现超调的现象,提高系统在参数摄动时的鲁棒性,采用自抗扰控制取代传统速度环中的比例积分(proportional integral,PI)控制、白鲸算法优化自抗扰控制参数,从而降低人工整定参数的复杂度;同时采用无模型控制电流环及模型预测与超局部模型结合的方法,设计一款滑模观测器。最后通过Matlab/Simulink软件进行仿真实验,由仿真结果可知:电机启动时超调较小,在负载突变时转速能够快速恢复到稳态;转速波动由原来的4.33%降低至3.85%,且达到稳态的时间显著减少,由200 ms降低至5 ms,电流脉动仅为±0.35 A。

基于SOA优化的ADRC胎面卷取张力控制系统

胎面卷取张力控制的精度直接影响后期成型工序的精度和硫化成品质量。为保证胎面成品的质量,以挤出联动线卷取时的张力控制为研究对象,针对胎面制品卷取速度和时变卷径引起的张力波动问题,首先分析系统张力产生机理,建立张力系统的数学模型,设计了系统启动和运行阶段的张力观测算法。其次建立仿真模型在系统启动-运行阶段通过对比自抗扰控制器(active disturbance rejection control,ADRC)与比例-积分-微分(proportional integral derivative,PID)的控制性能,验证了自抗扰控制响应速度快,能够稳定地控制张力,并且具备出色的抗干扰性和抗内部参数扰动能力。最后采用人群搜索算法(seeker optimization algorithm,SOA)筛选控制器参数最优值,将控制器应用到张力系统模型,仿真验证了所设计的人群搜索自抗扰控制策略的有效性和准确性。结果表明:SOA优化性能较好且与ADRC相结合的控制方式控制效果较佳。研究结果在桂林橡胶设计院的工艺方法及性能指标体系上进行控制算法设计,对实际生产具有一定的参考价值。

Feedforward and feedback optimal control for linear time-varying systems with persistent disturbances

The optimal control problem for linear time-varying systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions is consider and a design procedure of a feedforward and feedbaek optimal controller is presented. The condition of existence and uniqueness of the control law is given. The disturbanee observer is proposed to make the feedforward control law realizable physically. Simulation results demonstrate that the feedforward and feedbaek optimal control law is more effective and robust than the elassical state feedbaek control law with respect to external disturbanees.

基于双层CESO的电液伺服系统线性自抗扰控制

针对含高频噪声的阀控非对称缸不确定扰动抑制问题,采用扰动频率分层技术,利用线性扩张状态观测器低通滤波特性以及扰动估计速度和精度与带宽取值正相关性的特点,提出一种基于双层级联扩张状态观测器的阀控非对称缸电液伺服系统线性自抗扰方法。在分析双层级联线性扩张状态观测器稳定性基础上,与传统线性自抗扰控制方法进行了仿真对比研究。仿真结果表明:该控制方法继承了传统自抗扰控制优点,提高了不确定扰动估计速度和精度,有效抑制了含高频测量噪声不确定扰动带来的不利影响,可实现阀控非对称缸电液伺服系统的高性能控制。

基于IGWO-MPC和NDO-ISMC级联算法的UUV轨迹跟踪控制器设计

为了解决水下机器人(UUV)在受海流等复杂干扰力影响时的轨迹跟踪问题,设计了一种基于改进灰狼算法的模型预测控制(IGWO-MPC)和基于非线性干扰观测器的积分滑模控制(NDO-ISMC)级联的轨迹跟踪控制器。基于MPC方法设计了运动学控制器,提出利用在GWO算法中引入非线性收敛因子,基于个体经验和权重更新灰狼位置,以及反向学习策略所设计出的IGWO算法,来优化MPC的滚动优化求解过程,使机器人以期望的最优速度对给定位姿进行跟踪。基于IGWO-MPC运动学控制器得到的期望速度指令,设计了NDO-ISMC动力学控制器,该控制器利用NDO对干扰力进行估计,并对ISMC动力学输出控制律进行补偿以抑制扰动对跟踪精度的影响,同时输出扰动条件下机器人能够稳定跟踪上期望速度的控制推力。最后,利用MATLAB进行三维空间环境仿真,验证文章提出的将IGWO-MPC与NDO-ISMC算法级联的轨迹跟踪控制器能够使UUV在复杂水下环境下实现精确且稳定的轨迹跟踪。

基于扰动观测器和鲁棒模型预测的电动汽车集群调频方法研究

提出1种适用于高渗透率可再生能源孤岛型电网中大量电动汽车EVs(electric vehicles)的频率调节方法。首先,针对系统的降阶模型设计了扰动观测器,为聚集的电动汽车产生附加频率控制信号。该降阶模型通过结合负荷、风电、光伏系统和聚集电动汽车的变化而获得,可以产生1个由扰动观测器估计的集总扰动;然后,提出1种基于Tube模型的鲁棒预测控制RMPC(robust model predictive control)方法,以提供有效的控制信号,提高聚合后电动汽车的响应能力。控制信号的产生是为了以最小的控制动作获得频率偏差误差的最小值,同时考虑各种系统运行物理约束;接着,通过稳定性分析研究了时延对通信链路的影响,获得了时延裕度;最后,通过仿真分析验证了所提方法的有效性,并验证了所提方法相对于传统MPC、模糊比例积分控制和线性二次调节器控制的优越性。

基于干扰观测器的复杂非线性系统优化控制方法

为了提高具有未知干扰的复杂非线性系统的控制性能和运行性能,提出了一种基于干扰观测器的复杂非线性系统优化控制方法(IOCM).该方法设计了一个基于模糊神经网络的模型逼近器来捕捉系统的非线性动力学,并利用干扰观测器来描述系统的未知干扰,以获得更准确的系统预测模型.然后,在多目标模型预测控制的框架下,提出了一种具有协同成本函数和多梯度算法的优化控制结构,以综合求解设定点和控制律.采用城市污水处理过程基准仿真平台(BSM1)验证所提方法的有效性.实验结果表明:暴雨天气条件下平均出水水质(EQ)为6711 mg/L、平均运行能耗(EC)为3805 kW·h;对比其他分步实现的优化控制方法,IOCM具有较好的鲁棒性,能够提高非线性系统的优化控制性能.

Optimal deterministic disturbances rejection for singularly perturbed linear systems

Optimal deterministic disturbances rejection control problem for singularly perturbed linear systems is considered. By using the slow-fast decomposition theory of singular perturbation, the existent and unique conditions of the feedforward and feedback composite control （FFCC） laws for both infinite-time and finite-time are proposed, and the design approaches are given. A disturbance observer is introduced to make the FFCC laws realizable physically. Simulation results indicate that the FFCC laws are robust with respect to external disturbances.

稻麦联合收割机变频驱动液压控制中强扰动问题解决方法

稻麦联合收割机变频驱动液压泵,作为收割机液压系统中重要的动力元件,其在工作中存在非线性时变特征干扰,控制过程中存在的强扰动一直是需要解决的难点,提出一种稻麦联合收割机变频驱动液压控制方法。针对非线性时变特征带来的强扰动问题,设计了降阶负载扰动观测器与转速模糊控制器。将降阶负载扰动观测器、转速模糊控制器与工控计算机、变频器、发动机、液压泵等组件结合起来,构建了强干扰下变频驱动液压泵的自动化控制方法,实现了对液压系统中压力和流量的精确控制。实验结果表明:由该技术控制的收割机转速与流量相对稳定,具有较强的抗干扰性,泵出口压力与最大负载压力的压差较小,高度拟合,且几乎没有溢流损耗,节能效果显著。

逆变器高频谐波扰动电子信号自动检测方法

研究逆变器高频谐波扰动电子信号自动检测方法。构建逆变器的电子信号采样函数,获取电子信号采样结果。利用改进后的阈值函数对电子信号进行小波去噪处理,通过混合字典对去噪后的信号进行稀疏分解,确定电子信号高频谐波扰动特征。利用BFGS校正拟牛顿算法优化BP神经网络的梯度和参数,将电子信号高频谐波扰动特征输入优化BP神经网络中,得到逆变器高频谐波扰动电子信号自动检测结果。实验结果表明,所提方法能精准获取逆变器电子信号,对高频谐波扰动电子信号的检测误差小,效果好。

基于粒子群算法优化的汽车天窗改进型自抗扰控制

针对当前汽车天窗继电器闭合后,电动机控制天窗平移开闭、起翘开闭及防夹回退响应滞后问题,将内部不确定因素和外部环境干扰视为一个综合影响因素,提出了一种基于粒子群算法优化的改进型自抗扰控制方法,旨在改善汽车天窗的响应性能。首先,设计了一种新型cfal函数,解决了fal函数在拐点处不平滑容易引发抖动和控制系统不稳定的问题。接着,基于这种新型非线性cfal函数,构建了改进型扩张状态观测器,实现了对天窗扰动影响的实时估计。最后,采用粒子群算法进行内部参数优化调节,进行了汽车天窗系统的控制实验,并将该方法的输出响应曲线与传统ADRC控制进行了对比分析,实验结果验证了这种自抗扰控制方法在提升汽车天窗响应性能方面的优越性和可行性。

A modified active disturbance rejection control for a wastewater treatment process

Waste water treatment process(WWTP)control has been attracting more and more attention.However,various undesired factors,such as disturbance,uncertainties,and strong nonlinear couplings,propose big challenges to the control of a WWTP.In order to improve the control performance of the closed-loop system and guarantee the discharge requirements of the effluent quality,rather than take the model dependent control approaches,an active disturbance rejection control(ADRC)is utilized.Based on the control signal and system output,a phase optimized ADRC(POADRC)is designed to control the dissolved oxygen and nitrate concentration in a WWTP.The phase advantage of the phase optimized extended state observer(POESO),convergence of the POESO,and stability of the closed-loop system are analyzed from the theoretical point of view.Finally,a commonly accepted benchmark simulation model no.1.(BSM1)is utilized to test the POESO and POADRC.Linear active disturbance rejection control(LADRC)and the suggested proportion-integration(PI)control are taken to make a comparative research.Both system responses and performance index values confirm the advantage of the POADRC over the LADRC and the suggested PI control.Numerical results show that,as a result of the leading phase of the total disturbance estimation,the POESO based POADRC is an effective and promising way to control the dissolved oxygen and nitrate concentration so as to ensure the effluent quality of a WWTP.

DESIGN OF DISTURBANCE DECOUPLED FILTER AND ITSAPPLICATION TO MANEUVERING TARGETS TRACKING

A novel disturbance decoupled filter (DDF) design scheme is presented. Firstly, the system with unknown input is translated into an equivalent system without unknown imputs by a simple algebraic transformation. Then, a new DDF design scheme, which is very simple, is proposed via innovations theorem. At last, the application of DDF to Maneuvering Targets Tracking is simulated and the simulation results show that DDF is suitable for high maneuvering cases.