Coordinating optimization-based sliding mode variable structure control for electro-hydraulic servo system

A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.

Time-varying Sliding Mode Controls in Rigid Spacecraft Attitude Tracking

To solve the problem of attitude tracking of a rigid spacecraft with an either known or measurable desired attitude trajectory, three types of time-varying sliding mode controls are introduced under consideration of control input constraints. The sliding surfaces of the three types initially pass arbitrary initial values of the system, and then shift or rotate to reach predetermined ones. This way, the system trajectories are always on the sliding surfaces, and the system work is guaranteed to have robustness against parameter uncertainty and external disturbances all the time. The controller parameters are optimized by means of genetic algorithm to minimize the index consisting of the weighted index of squared error （ISE） of the system and the weighted penalty term of violation of control input constraint. The stability is verified with Lyapunov method. Compared with the conventional sliding mode control, simulation results show the proposed algorithm having better robustness against inertia matrix uncertainty and external disturbance torques.

Disturbance observer based time-varying sliding mode control for uncertain mechanical system

It is now well known that the time-varying sliding mode control （TVSMC） is characterized by its global robustness against matched model uncertainties and disturbances. The accurate tracking problem of the mechanical system in the presence of the parametric uncertainty and external disturbance is addressed in the TVSMC framework. Firstly, an exponential TVSMC algorithm is designed and the main features are analyzed. Especially, the control parameter is obtained by solving an optimal problem. Subsequently, the global chattering problem in TVSMC is considered. To reduce the static error resulting from the continuous TVSMC algorithm, a disturbance observer based time-varying sliding mode control （DOTVSMC） algorithm is presented. The detailed design principle and the stability of the closed-loop system under the composite controller are provided. Simulation results verify the effectiveness of the proposed algorithm.

Exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and mode-dependent probabilistic time-varying delays

In this paper, the problem of exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and Mode-dependent probabilistic time-varying coupling delays is investigated. The sam- pling period is assumed to be time-varying and bounded. The information of probability distribution of the time-varying delay is considered and transformed into parameter matrices of the transferred complex dynamical network model. Based on the condition, the design method of the desired sampled data controller is proposed. By constructing a new Lyapunov functional with triple integral terms, delay-distribution-dependent exponential synchronization criteria are derived in the form of linear matrix inequalities. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

Sliding mode control for mobile welding robot

The sliding mode controller of mobile welding robot is established in this paper through applying the method of variable structure control with sliding mode into the control of the mobile welding robot. The traditional switching function smooth method is improved by combining the smoothed switching function with the time-varying control gain. It is shown that the proposed sliding mode controller is robust to bounded external disturbances. Experimental results demonstrate that sliding mode controller algorithm can be used into seam tracking and the tracking system is stable with bounded uncertain disturbance. In the seam tracking process, the robot moves steadily without any obvious chattering.

永磁同步电机改进积分型时变滑模控制

为了提高永磁同步电机的控制性能,改善对于电机的控制方法,针对永磁同步电机的积分滑模控制进行研究,首先,提出积分滑模控制在运行中遭遇未知干扰后易产生转速超调的问题。然后,通过定义自调节的积分初值来消除运行过程中因积分累积所产生的超调,改善转速超调问题。其次,为了提高滑模控制在电机整个运动的全局阶段的收敛性,提出基于预测在线寻优的时变滑模控制,通过预测控制变量来选出当前时刻的最优滑模面,使得状态变量可以更快收敛到滑模面,进一步降低转速误差,提高系统的控制精度与控制速度。最后,建立扩张状态观测器来观测系统的未知干扰,对控制器进行补偿,提高整个控制系统的鲁棒性,并且通过仿真和实验验证了所提出方法的有效性。

Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time.

Robust stability analysis for Markovian jumping stochastic neural networks with mode-dependent time-varying interval delay and multiplicative noise

This paper is concerned with the problem of robust stability for a class of Markovian jumping stochastic neural networks （MJSNNs） subject to mode-dependent time-varying interval delay and state-multiplicative noise. Based on the Lyapunov-Krasovskii functional and a stochastic analysis approach, some new delay-dependent sufficient conditions are obtained in the linear matrix inequality （LMI） format such that delayed MJSNNs are globally asymptotically stable in the mean-square sense for all admissible uncertainties. An important feature of the results is that the stability criteria are dependent on not only the lower bound and upper bound of delay for all modes but also the covariance matrix consisting of the correlation coefficient. Numerical examples are given to illustrate the effectiveness.

基于改进非线性滑模控制的轮式机器人轨迹跟踪

针对轮式机器人的轨迹跟踪控制存在的问题,设计了一种改进非线性快速终端滑模控制器(improved nonlinear fast terminal sliding mode controller,INFTSMC)的控制方案。首先,通过对轮式机器人运动学的分析建立了轨迹跟踪误差模型;其次,在设计滑模控制器阶段,针对非线性快速终端滑模控制器存在奇异点,采用一种新的滑模面幂指数时变策略来设计非奇异终端滑模控制器,解决了非线性快速终端滑模控制器奇异问题,通过构造Lyapunov函数进行稳定性分析证明了该策略的稳定性,并且进行收敛时间分析给出系统从任意初始状态收敛至平衡点所需要的时间;然后,在新的滑模面幂指数时变策略的基础上设计了轮式机器人线速度和角速度控制律,使得轮式机器人轨迹跟踪误差快速收敛至0,实现了移动机器人对期望轨迹的快速跟踪。通过仿真实验与非线性快速终端滑模控制器和传统滑模控制其进行对比,验证了改进非线性快速终端滑模控制器的优越性。

基于DOB和反演时变滑模的PMSM位置跟踪

针对传统反演滑模位置伺服系统中位置跟踪误差较大,以及采用固定滑模面时系统动态响应速度和抖振抑制之间的矛盾,设计了一种基于扰动观测器和反演时变滑模的复合控制策略。首先在传统指数趋近律中引入状态变量并设计自适应律,提出一种新型趋近律,来提升系统的响应性能。为进一步提升系统在各个阶段的收敛速度,利用预测控制中遍历寻优思想,设计一种在线寻优的时变滑模面,并进行稳定性证明。最后设计非线性负载干扰观测器,对系统进行干扰估计与补偿。实验数据表明,本文所提复合控制策略与传统反演滑模控制相比,其稳态误差仅占传统方法的9/17,动态响应速度提升了30 ms,抗扰性能明显优越。

采用TVFEMD和瞬时能量比的轧辊磨床颤振在线监测方法

在磨削过程中,颤振是轧辊表面产生振纹的一个最重要的原因,严重影响了工件表面质量。为避免颤振带来的不利影响,提出了一种基于时变滤波经验模态分解(TVFEMD)和瞬时能量比的(IER)的颤振在线监测方法。该方法采用可靠的指标提前监测出颤振的发生,解决了轧辊磨床早期颤振特征微弱,在背景噪声下难以快速识别的问题。首先对实时采集的振动信号进行实时分段处理。其次对每个砂轮转动周期内的信号进行时变滤波经验模态分解,提高信噪比。然后运用瞬时频率和瞬时能量比选取颤振敏感频带,将颤振敏感频带的瞬时能量比作为颤振特征。最后基于瞬时能量比上升量确定颤振监测阈值,判断当前加工状态。试验结果表明,在不同的轧辊磨床加工条件下,所提方法均能在颤振过渡阶段将其检测出来,更快地实现颤振早期预警;与EMD等传统时频分析方法相比,在早期颤振监测中具有明显的优势。

基于VMDT-POA-DELM-GPR的两阶段短期负荷预测

针对传统负荷预测方法精度不高的问题,为准确捕捉到负荷数据波动的规律,提出了一种两阶段负荷预测方法。第1阶段首先用变分模态分解(VMD)对原始负荷序列进行分解,得到分解处理后的残差分量,再采用时变滤波经验模态分解(TVF-EMD)方法进行特征提取;然后对全部子序列分别建立深度极限学习机(DELM)模型,同时利用鹈鹕优化算法(POA)进行参数寻优,叠加各子序列的预测值得到初始负荷预测值。第2阶段采用POA-DELM模型对误差分量进行预测;然后将第一阶段中所有子序列预测值和误差预测值作为特征输入到高斯过程回归(GPR)模型中,得到负荷最终的预测结果。结果表明,两阶段模型的均方根误差(RMSE)、平均绝对误差(MAE)分别为对比模型的4%~77%、4%~76%,而平均百分比误差(MAPE)仅为0.0678%,可有效提高电力负荷的预测精度。

基于TVFEMD-IMF能量熵增量的桥梁监测数据降噪方法

针对桥梁监测数据受多重噪声干扰、影响结构真实响应获取的问题,提出了一种基于时变滤波经验模态分解(time-varying filtering empirical mode decomposition,简称TVFEMD)和本征模函数(intrinsic mode function,简称IMF)能量熵增量的桥梁监测数据降噪方法。首先,利用TVFEMD分解桥梁原始监测数据,得到多个子序列;其次,采用IMF能量熵增量确定多个子序列中的有效子序列;然后,划分子序列中的结构响应分量和噪声分量,对结构响应分量重组实现监测数据降噪;最后,利用平均绝对误差(mean absolute error,简称MAE)、均方根误差(root mean squared error,简称RMSE)和信噪比(signal-noise ratio,简称SNR)对不同方法的降噪效果进行评价。仿真算例和工程实例结果表明:TVFEMD相比经验模态分解(empirical mode decomposition,简称EMD),有效解决了模态混叠问题;TVFEMD结合IMF能量熵增量方法,有效抑制了多重噪声影响,对结果精度有较大提升;与EMD-IMF能量熵增量和Kalman滤波降噪法相比,TVFEMD-IMF能量熵增量法所得到降噪信号的MAE和RMSE值分别提升了23%和21%以上,降噪效果更好,信噪比提升38%以上,抗噪性能更佳。

基于TVFEMD和多模型融合的变压器油中溶解气体体积分数预测方法

油中溶解气体分析可以反映变压器的运行状态,对其体积分数精准预测可以为变压器早期故障判别和预警提供理论支撑。为此提出了一种基于时变滤波经验模态分解和多模型融合的变压器油中溶解气体体积分数预测方法。首先,通过时变滤波经验模态分解将气体体积分数序列分解为多个子序列,降低其非平稳性;其次,利用多模型融合策略,将4种不同单模型的预测结果进行融合重构,因单模型权重系数对预测结果有显著影响,利用改进黏菌算法对权重系数进行优化,以提高预测精度;最后,通过算例验证表明,相比于传统的预测模型,所提方法具有更高的预测精度,可以更好地预测油中气体体积分数的变化趋势。

充液挠性航天器时变滑模控制及振动抑制

针对存在外界未知干扰、参数不确定问题的刚-液-柔多体耦合航天器姿态控制进行了研究.将液体燃料的晃动等效为球摆模型,挠性附件假设为欧拉-伯努利梁,建立了多体耦合航天器动力学方程.首先,设计了积分滑模干扰观测器,使其能够在有限的时间范围内对控制系统的集总扰动实现准确估计;其次,以此干扰观测器为基础,设计了一种时变滑模控制方法,该控制运用双曲正切函数;最后,结合光滑整形技术,设计出零振动指令光滑器,从而抑制液体晃动和挠性附件振动.数值仿真结果表明:本文所设计的控制方案具有可行性和有效性,多模态充液挠性航天器在姿态机动过程中所引起的残余振动可以得到有效抑制.

基于变速趋近律的PMSM复合速度控制

为了提高永磁同步电机速度控制器的性能,文章提出一种新型变速趋近律滑模控制策略。变速趋近律在传统指数趋近律的基础上引入关于系统状态的幂次项和关于滑模函数的变速项,并采用双曲正切函数来减小高频切换项的影响。该控制策略有利于减小电流和转矩脉动,提高了系统运行的稳定性和响应速度。另外,针对系统受未知干扰影响的问题,设计了一种滑模扰动观测器来估计系统的总扰动,并将估计的扰动补偿到复合速度控制器中。最后,利用Matlab/Simulation仿真和电机实验平台对所提出的控制策略进行验证。仿真和实验结果表明,复合速度控制器与扰动观测器相结合的控制策略具有更快的收敛速度、更小的抖振和更好的抗扰性能。

基于改进TVF-EMD与SVD的轴承故障特征提取

滚动轴承早期故障信号微弱,故障特征难以提取。针对此问题,提出一种基于时变滤波经验模态分解(TVF-EMD)模态分量自适应融合与奇异值分解(SVD)降噪的轴承早期故障特征提取方法。为了降低故障信号的非线性和非平稳性,通过TVF-EMD将轴承信号分解为一系列本征模态函数(IMF)。为了克服TVF-EMD分解后IMF分量过多的不足,构造包络故障信息能量占比(EREFI)指标,通过EREFI对IMF分量进行降序排列,并依据包络故障信息能量占比递增原则对IMF分量依次进行融合,直至找到最优融合分量。最后,通过SVD对最优融合分量降噪,并提取故障特征。通过仿真信号以及2个实测轴承故障信号对所提方法性能进行了实验验证。实验结果表明:所提方法具有良好的敏感特征筛选融合能力和降噪能力,能更准确提取出轴承早期故障特征,实现故障类型的准确识别。

基于时变滤波经验模态分解的非接触式心率变异性估计方法

民航从业人员的身体健康状况是影响航空安全的重要因素,其中呼吸和心跳是极其重要的健康状况表征。为解决接触式或穿戴式测量系统对人员工作时的局限与影响,可采用线性调频连续波(Frequency-modulated continuous wave,FMCW)雷达达到非接触式测量的目的。由于生命体征信号具有时变、非平稳的特点,针对经验模态分解(Empirical mode decomposition,EMD)在信号分解中存在模态混叠现象的问题,使用时变滤波经验模态分解(Time varying filtering based on EMD,TVF-EMD)自适应信号的局部截止频率,可有效提高信号分离性能,解决模态混叠问题。利用TVF-EMD分解出的本征模态函数(Intrinsic mode functions,IMF)分量重构心跳对应的时域信号,估计心跳信号的频率和心跳节拍间隔(Inter-beat interval,IBI),进一步对心率变异性(Heart rate variability,HRV)相关指标进行估计。仿真实验与实测数据处理结果表明,TVF-EMD可从毫米波雷达测量信号中有效分离出呼吸与心跳信号。同时,从模态混叠程度及信号分离性能两方面对TVF-EMD与EMD方法分解效果进行了仿真分析,结果表明TVF-EMD能够有效解决模态混叠问题。因此,TVF-EMD方法能够准确有效地从毫米波雷达测量信号中提取生命体征信息,为IBI估计和HRV分析提供准确的时域信息,具有广阔的应用前景。

基于模糊时变滑模的永磁同步电机调速系统设计

针对永磁同步电机突然加入负载时存在的转速波动和不稳定问题,提出一种基于积分时变滑模面和新型模糊增益趋近律的滑模调速方法。采用积分时变滑模面,在传统积分滑模面中加入一个时变项,借此提升系统的响应速度。改进传统的指数趋近律,加入非线性函数来削弱系统的抖振,同时根据不同的系统状态用模糊算法整定趋近律增益参数,着重于提升趋近速度和系统抗扰动能力。最后,使用李雅普诺夫稳定性判据证明了该控制系统的稳定性。在MATLAB/Simulink环境下将此控制策略与传统滑模控制策略进行对比,仿真结果表明:采用此控制方法的系统响应速度更快、抑制系统扰动和抖振的能力更强,具备更好的综合性能。

可控换相换流器耗能模式工作原理及电气建模

可控换相换流器(controllableline-commutedconverter,CLCC)具备可控关断能力,能够消除交流系统单相接地引起的换相失败故障,但是故障期间,直流传输功率仍会下降;为此,提出了CLCC主避雷器和V13子阀避雷器充当耗能电阻的耗能模式工作原理,建立了阀避雷器非线性时变电压源模型,求解了耗能模式下CLCC工作电路电气方程,确定了V13子阀避雷器残压值和阀提前关断时间对耗能功率的影响规律,搭建了包含维持系统传输功率为恒定值的闭环控制策略直流系统仿真模型,证明了CLCC在发挥换流作用的同时充当直流耗能装置,逆变站交流系统无法消纳的功率可由CLCC消耗掉,系统的直流功率将不会发生波动,可以把逆变站交流系统单相接地故障对直流系统的冲击降至最小。