基于多观测器的一类过驱动系统主动容错控制设计

以四旋翼直升机姿态控制系统为对象,针对一类过驱动系统,由控制分布阵列不满秩而引起的执行器故障诊断难的问题,本文采用了一种新颖的多观测器故障诊断方法对执行器故障进行检测和估计,进而设计一种具有故障补偿并且满足H∞性能的动态输出反馈跟踪控制器。该方法不仅能够快速的检测和估计出单通道执行器故障,而且能够有效的补偿故障对系统稳定性的不利影响,保证系统在单通道执行器故障下具有一定的姿态跟踪能力。相对于状态反馈控制器,所提算法有效的避免了模拟状态量而带来的误差,一定程度上提高了系统的控制精度和可实现性。最后通过Quanser3-DOF Hover半物理仿真平台验证所提算法的可行性和有效性。

基于联合多观测器的四旋翼直升机故障诊断

针对四旋翼飞行器在发生执行器故障情况下难以进行故障估计的问题,基于增广故障估计观测器和Luenberger故障检测观测器,提出了一种较为新颖的联合多观测器的故障诊断设计方法。该设计方法不仅能够有效地估计单通道执行器故障,解决故障分布阵列不满秩问题下故障估计难的问题,而且拓宽了增广故障估计观测器的适用范围。最后,通过Quanser 3-DOF Hover平台验证了所提算法的可靠性和有效性。

基于故障描述因子与多观测器同步协作的AUV执行机构故障隔离与辨识

执行机构的可靠性对系统的安全运行具有重要意义.针对自主式水下机器人(AUV),提出一种基于故障描述因子与多观测器同步协作的故障隔离与辨识方法.首先,通过执行机构故障描述因子概念的引入,将AUV运载器的故障隔离和辨识问题分为两个层级;其次,通过扩张状态观测器(ESO)和故障隔离逻辑规则的设计,实现包括舵面、螺旋桨与舵机在内的粗粒度级执行机构的故障隔离;然后,根据故障力与力矩的正负性关系,进一步分析舵面的具体形变故障类型,亦或基于螺旋桨与舵机的输出力与力矩关系,通过分析故障因子的内部信息,具体辨识可能的螺旋桨与舵机故障类型;最后,通过仿真结果表明所提出方法对AUV执行机构的故障具有较好的隔离与辨识精度.

基于PSO的多观测器轨迹优化研究

在多观测站目标被动跟踪过程中,多观测器运动轨迹对定位跟踪精度有重要影响。为提高对运动目标的跟踪精度,将目标滤波协方差的迹作为目标优化函数,提出一种基于粒子群算法(Particle Swarm Optimi-zation,PSO)的多观测器轨迹优化方法,并将轨迹优化加入运动目标被动跟踪过程中,实现了观测器自适应运动下的运动目标被动跟踪。在借鉴单站测角被动跟踪轨迹优化基本规则的基础上,给出多观测器偏航角约束条件,有效减小了优化算法搜索范围,提高了算法效率。针对目标转弯机动进行仿真研究,结果表明该算法可以有效减小对机动目标的位置、速度及角度跟踪误差,并分析得出多观测器的基本运动趋势。

基于多模型参数估计的舵机故障诊断算法

为了实现无人机舵机工作状态的在线监测,实时提供故障类型与故障程度,设计了一种基于多模型参数估计的舵机故障诊断算法。首先描述了舵机各典型故障类型的动态特性,并建立相应的故障模型。然后就各故障类型设计相应的故障状态观测器及参数估计器,实时监测舵机运行状态,在舵机出现故障时能够及时给出故障信息。同时设计多观测器切换机制,以解决多个观测器的选取问题。仿真结果表明,建立的故障模型能够很好地描述典型故障的动态特性,多观测器切换机制能够及时准确地切换至最接近当前舵机状态的观测器,给出最接近实际情况的故障信息。

机载雷达组网多站测角被动跟踪轨迹优化研究

研究多观测器轨迹优化控制问题,由于多站测角被动跟踪系统运行存在误差,用机载雷达组网的可移动传感器采集信息,可对雷达载体轨迹优化进行研究,利用控制雷达载体的飞行轨迹可有效解决跟踪目标的弱观测性及估计器的稳定性。为了改善传统轨迹优化算法容易陷入早熟收敛和局部最小的问题,提出一种模拟退火(Simulated Annealing,SA)和粒子群优化(Particle Swarm Optimization,PSO)算法的混合优化方法(SA-PSO)。在给出了角度信息的适应度函数表达式基础上,结合模拟退火算法的局部搜索能力和粒子群优化算法的全局搜索能力,提高优化算法的收敛速度、精度以及全局搜索能力。实验证明,改进的混合算法对雷达载体轨迹优化有效,并减小对机动目标的被动跟踪误差。

ROBUST FAULT DIAGNOSIS FOR HELICOPTER FCS BASED ON LINEAR PARAMETERVARYING ADAPTIVE OBSERVER

Based on the linear parameter-varying （LPV） adaptive observer, the robust fault diagnosis for a class of LPV systems with external disturbances is studied. Since the flight control system （FCS） is nonlinear and time-varying, the LPV technique is used for FCS. And then the adaptive fault estimation algorithm based on the LPV adaptive observer is proposed to estimate the fault. To minimize the effect of disturbances on the fault estimation, the H~ robust performance index is introduced to design the LPV adaptive fault diagnosis observer and the fault estimation algorithm. The result shows that the method has good estimation performance and is robust to external disturbances. The design method is presented in terms of linear matrix inequalities （LMIs）. Finally, a helicopter LPV FCS model with the actuator fault is used to illustrate the effectiveness of the proposed method.

Fast integrated guidance and control with global convergence

A global fast convergent integrated guidance and control design approach is proposed. A disturbance observer is utilized to estimate the uncertainties of integrated guidance and control model in finite time. According to the multiple sliding-mode surface control, the independent nonsingular terminal sliding functions are presented in each step, and all the sliding-mode surfaces run parallel. These presented sliding-mode surfaces keep zero value from a certain time, and the system states converge quickly in sliding phase. Therefore, the system response speed is increased. The proposed method offers the global convergent time analytically, which is useful to optimize the transient performance of system. Simulation results are used to verify the proposed method.

Multimodal alarm behavior in urban and rural gray squirrels studied by means of observation and a mechanical robot

Urbanization of animal habitats has the potential to affect the natural communication systems of any species able to survive in the changed environment. Urban animals such as squirrels use multiple signal channels to communicate, but it is un- known how ttrbanization has affected these behaviors. Multimodal commtmication, involving more than one sensory modality, can be studied by use of biomimetic mechanical animal models that are designed to simulate the multimodal signals and be pre- sented to animal subjects in the field. In this way the responses to the various signal components can be compared and contrasted to determine whether the multimodal signal is made up of redundant or nonredundant components. In this study, we presented wild gray squirrels in relatively urban and relatively rural habitats in Western Massachusetts with a biomimetic squirrel model that produced tail flags and alarm barks in a variety of combinations. We found that the squirrels responded to each unimodal component on its own, the bark and tail flag, but they responded most to the complete multimodal signal, containing both the acoustic and the moving visual components, providing evidence that in this context the signal components are redundant and that their combination elicits multimodal enhancement. We expanded on the results of Partan et al. （2009） by providing data on sig- naling behavior in the presence and absence of conspecifics, suggesting that alarm signaling is more likely if conspecifics are present. We found that the squirrels were more active in the urban habitats and that they responded more to tail flagging in the urban habitats as compared to the rural ones, suggesting the interesting possibility of a multimodal shift from reliance on audio to visual signals in noisier more crowded urban habitats [Current Zoology 56 （3）： 313-326, 2010].

ESO-based decoupling control with multi-objective optimization for boiler-turbine unit

A model-assistant extended state observer(MESO)-based decoupling control strategy is proposed for boiler-turbine units in the presence of unknown external disturbance and model-plant mismatch. For ease of implementation, the decoupling compensator is reduced to the proportion integration(PI) decoupler with the frequency domain analysis, where the decoupling error in collusion of uncertainties and disturbances can be estimated by the proposed MESO and then compensated. To decrease the sensitivity of the dynamic error for the decoupling control and fulfill various requirements of constraints, such as safety operation, energy conservation, emission reduction, etc., the plant is transmitted through a scheduled steady state region which is achieved from the optimized reference governor in advance. Simulation results show that the proposed control strategy can well suppress various disturbances including a decoupling error, and multi-objective optimization can meet multiple requirements with the premise of safety production.

Cooperative output tracking of multi-agent systems under finite time

The cooperative output tracking problem of multi-agent systems in finite time is considered.In order to enable the agents to quickly track and converge to external system within a finite time,a novel distributed output feedback control strategy based on the finite-time state observer is designed.This distributed finite-time observer can not only solve cooperative output tracking problems when the agents can not get external system signal,but also make the systems have a faster convergence and a good robustness.The stability of the system in finite time is proved based on Lyapunov function.Numerical simulations results have been provided to demonstrate the effectiveness of the proposed protocol.