Adaptive sliding mode control for limit protection of aircraft engines

In practice, some sensors of aircraft engines naturally fail to obtain an acceptable measurement for control propose, which will severely degrade the system performance and even deactivate the limit protection function. This paper proposes an adaptive strategy for the limit protection task under unreliable measurement. With the help of a nominal system, an online estimator with gradient adaption law and low-pass filter is devised to evaluate output uncertainty. Based on the estimation result, a sliding mode controller is designed by defining a sliding surface and deriving a control law. Using Lyapunov theorem, the stability of the online estimator and the closed-loop system is detailedly proven. Simulations based on a reliable turbofan model are presented, which verify the stability and effectiveness of the proposed method. Simulation results show that the online estimator can operate against the measurement noise, and the sliding controller can keep relevant outputs within their limits despite slow-response sensors.     

具有丢包补偿的分布式一致性融合估计器

研究了具有随机丢包的网络化分布式一致性估计问题。丢包现象存在于各节点间局部状态估计值的传输过程中,引入一组服从Bernoulli分布的随机变量来描述。当发生丢包时,以融合节点前一时刻融合估计值的一步预测值进行补偿。建立了以估计器增益为决策变量,以所有传感器有限时域下状态融合估计误差和为代价函数的优化问题。在给定一致性权重下,通过最小化代价函数的上界得到了一组次优的估计器增益,并给出了融合估计器渐进稳定的充分条件。最后,通过算例仿真验证了算法的有效性。     

MAP estimation of target manoeuvre sequence with theexpectation-maximization algorithm

Two algorithms are derived for the problem of tracking a manoeuvring target based on a sequence of noisy measurements of the state. Manoeuvres are modeled as unknown input (acceleration) terms entering linearly into the state equation and chosen from a discrete set. The expectation maximization (EM) algorithm is first applied, resulting in a multi-pass estimator of the MAP sequence of inputs. The expectation step for each pass involves computation of state estimates in a bank of Kalman smoothers tuned to the possible manoeuvre sequences. The maximization computation is efficiently implemented using the Viterbi algorithm. A second, recursive estimator is then derived using a modified EM-type cost function. To obtain a dynamic programming recursion, the target state is assumed to satisfy a Markov property with respect to the manoeuvre sequence. This results in a recursive but suboptimal estimator implementable on a Viterbi trellis. The transition costs of the latter algorithm, which depend on filtered estimates of the state, are compared with the costs arising in a Viterbi-based manoeuvre estimator due to Averbuch, et al. (1991). It is shown that the two criteria differ only in the weighting matrix of the quadratic part of the cost function. Simulations are provided to demonstrate the performance of both the batch and recursive estimators compared with Averbuch's method and the interacting multiple model filter     

飞机的模型参考容错控制

 本文针对飞机内部元件或控制元件的故障,用检测滤波器理论设计了相应的故障检测器和故障参数估计器,并用Lyapunov稳定性理论设计了模型参考自适应容错控制律,从而保证了在内部故障情况下飞行控制系统的稳定性。     

Reduced state estimators for consistent tracking of maneuvering targets

Linear Kalman filters, using fewer states than required to completely specify target maneuvers, are commonly used to track maneuvering targets. Such reduced state Kalman filters have also been used as component filters of interacting multiple model (IMM) estimators. These reduced state Kalman filters rely on white plant noise to compensate for not knowing the maneuver - they are not necessarily optimal reduced state estimators nor are they necessarily consistent. To be consistent, the state estimation and innovation covariances must include the actual errors during a maneuver. Blair and Bar-Shalom have shown an example where a linear Kalman filter used as an inconsistent reduced state estimator paradoxically yields worse errors with multisensor tracking than with single sensor tracking. We provide examples showing multiple facets of Kalman filter and IMM inconsistency when tracking maneuvering targets with single and multiple sensors. An optimal reduced state estimator derived in previous work resolves the consistency issues of linear Kalman filters and IMM estimators.     

On Optimal Control of Linear Systems in the Presence of Multiplicative Noise

This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programing. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an "enforced separation" solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.     

基于神经网络逆控制的发动机直接推力控制

首次将动态神经网络逆控制用于航空发动机直接推力控制。为了有效消除由于神经网络逆模型构造误差(即神经网络逆模型不可能完全逼近航空发动机的逆模型)而产生的稳态误差和解决航空发动机推力不易测量的困难,分别设计了积分补偿器和推力估计器,从而实现航空发动机直接推力控制。飞行包线内数字仿真结果表明,此控制方案具有良好的动静态性能、精度高、跟踪快。     

Reduced-order multiple model adaptive controller for flexiblespacestructure

The robustness of a moving-bank multiple model adaptive estimator/controller to order reduction in the controller design model is examined. It is shown that the adaptive mechanism and bank-moving logic are not confounded by the effects of unmodeled higher order modes of a large flexible spacestructure. Control characteristics are achieved that are essentially equivalent to those of an artificially informed benchmark controller     

Robust dissipative compensators for flexible spacecraft control

The problem of controller design for flexible spacecraft is addressed. Model-based compensators, which rely on the knowledge of the system parameters to tune the state estimator, are first considered, and are shown to have high sensitivity to parameter uncertainties. Three types of dissipative controllers, which use collocated actuators and sensors, are next considered. These controllers guarantee stability in the presence of unmodeled elastic modes and parameter uncertainties. A procedure is given for designing an optimal dissipative dynamic compensator, which can provide better performance while still retaining robust stability     

模糊控制理论在航空涡轮喷气发动机控制系统中的应用

对模糊控制进行了介绍。采用相平面法设计了模糊控制器,将其编成微机程序,使其完成模糊控制功能。对微机完成的其他操作,亦进行了介绍,给出了微机的主流程图。进行了多次发动机台架试车,当对发动机控制系统加入小偏离的控制和干扰信号,以及大偏离信号时,发动机的稳态和加速过程都获得了良好的控制品质。表明模糊控制具有满意的控制性能。     

基于机载实时模型的发动机执行机构 故障状态参数估计

为了对发动机的主燃烧室供油量控制器、喷管喉部面积控制器、风扇进口可调导叶角度控制器、压气机进口可调导叶角度控制器进行故障诊断,建立了基于简化n+1残量方法的非线性机载实时模型,并结合常增益扩展卡尔曼滤波器建立执行机构控制参数估计器,利用非线性部件级模型模拟飞行包线内发动机执行机构的软故障.仿真结果表明:执行机构控制参数估计器在飞行包线内能实现较高精度估计,且具有较好的稳定性.     

仿人智能开关算法在发酵温控中的应用

发酵温度对象具有严重非线性、时变不确定、大滞后等特点,且受环境温度影响非常大,目前微型发酵罐的全过程温度自动控制是个较难解决的问题。常规PID控制中的比例、积分、微分能够模拟人脑的功能,但缺乏智能性,控制效果不佳。针对此问题设计了仿人智能开关控制器,并在东北大学发酵实验室微型发酵罐温度控制中进行了应用。实验结果表明,仿人智能开关控制器比传统的PID控制器的控制精度更高、稳态性能更好,具有较高的应用价值。     

Sensorless synchronous reluctance drive with standstill starting

This paper presents a novel sensorless synchronous reluctance drive system. Based on the dynamic model of the synchronous reluctance motor (SRM), a new rotor position estimator is proposed. This estimator is only related to the rate change of the stator currents. It is not related to the parameters, speed, voltage, and external load of the motor. As a result, the estimator is simple and robust. Based on the proposed estimator, a sensorless synchronous reluctance drive has been implemented. This drive system can start from standstill and accelerate to a rated speed; the traditional open-loop starting method, therefore, is unnecessary. A digital signal processor, TMS-320-C30, is used to implement the estimating and control algorithms. Experimental results show that the proposed system works well. The adjustable speed range can be from 1 r/min to 1800 r/min. Moreover, by adding the position-loop controller the proposed system can perform as a position control drive as well. Several experimental results validate the theoretical analysis.     

基于多指标非线性控制的永磁同步电动机转速控制

应用精确线性化方法研究了永磁同步电动机的非线性控制问题.根据精确线性化理论,设计了永磁同步电动机状态反馈线性化控制器和相对阶为1的多指标输入输出反馈线性化控制器.多指标非线性控制器选择全状态量线性组合形式为输出函数,根据系统特征根配置方法,整定了输出函数中各状态量的反馈系数.比较2种控制器仿真结果发现,多指标非线性控制器可以实现对电动机转速的有效控制,且控制器结构简单,设计方便,动静态性能良好.     

Flexible spacestructure control via moving-bank multiple modelalgorithms

The development and performance of moving-bank multiple model adaptive control (MMAC) algorithms for quelling vibrations induced in the SPICE 2 space structure are presented. The structure consists of a large platform and a smaller platform connected by three legs in a tripod fashion. Deviations of the line-of-sight (LOS) vector from the center of the large platform to the center of the smaller platform are used for LQG controller performance evaluation. The parameter estimator implements the maximum entropy with identity covariance (ME/I) algorithm; the moving-bank logic employs parameter position monitoring; the controller uses the modified MMAC method. Whereas parameter variations of two percent caused instabilities in the single filter/controller design, the MMAC algorithm provides an excellent method to estimate a wide range of parameter variations and to quell oscillations in the structure     

On the Design of Suboptimal Controllers for Minimal Time Feedback Regulators

A method for designing suboptimal minimal time controllers for linear, time-invariant regulator systems is presented. An economical closed-loop controller is obtained by using Lyapunov surfaces, corresponding to a quadratic Lyapunov function, as a continuous approximation for isochronal surfaces. Systems employing this controller are obtained by minimization, with respect to parameters of the quadratic Lyapunov function, of the worst case upper bound on the arrival time of an arbitrary initial state at the origin.     

航空发动机控制系统性能恢复设计:H_∞/PR

对于航空发动机这样一类状态及输出矩阵存在摄动的系统,提出了一种直接根据性能指标作为恢复的目标的性能恢复理论设计方法。首先进行具有稳定及性能鲁棒性的状态反馈的H∞控制设计,然后通过设计一个状态观测器使得上述状态反馈控制的特性得以恢复。     

双重未知干扰解耦的多传感器系统偏差校正与状态估计

具有未知干扰输入的随机系统状态估计问题广泛存在于控制、通信、信号处理和故障诊断等领域,但目前的研究成果大多局限于单传感器动态离散系统。针对状态方程含有未知干扰、量测方程含有未知偏差的多传感器系统状态估计问题开展了研究,提出了一种双重未知干扰解耦下的最小方差无偏估计滤波器。首先,建立量测偏差通用演化模型;然后,解耦偏差演化模型中的未知输入,设计最小方差无偏估计器对量测干扰偏差进行估计;之后,利用估计出的量测偏差来校正动态系统测量值;最后,根据量测偏差校正后的系统模型设计最优状态观测器,获得具有最小方差无偏的状态估计。径向飞行控制系统的例子验证了所提方法的有效性,与相关方法的仿真对比反应了所提方法的优越性。     

一类不确定时滞模糊系统的保性能可靠控制

针对一类不确定时滞模糊系统,研究了执行器故障情况下的状态反馈保性能可靠控制问题。首先,在不确定时滞系统的T-S模糊模型的基础上,设计了状态反馈控制器;然后,选取保性能指标和构造Lyapunov函数,给出系统存在保性能可靠控制器的充分条件,并以线性矩阵不等式的形式表达。通过求解LMI方程就可以得到状态反馈保性能可靠控制器。采用所设计的保性能可靠控制器,当任意执行器出现故障时,闭环系统仍保持渐近稳定且保持原有的性能指标。     

广义预测自适应控制器在导弹控制系统设计中应用

将一种新的广义预测自适应控制算法应用于快速时变的导弹控制系统设计中。讨论了设计参数对控制系统性能的影响;针对自适应控制信号过大,提出了改进方案,增强了系统的鲁棒性和抗干扰能力。大量的数字仿真结果表明:运用该方案设计的导弹控制系统具有很好的跟踪性能和强的抗干扰能力;对系统阶次、参数、时延和采样周期的变化具有很强的鲁棒性;自适应算法中,对验前知识要求少,实现起来也比较简单。