模糊自适应的高超飞行器控制与干扰

针对具有超大飞行马赫数、超宽飞行包络、飞行环境复杂等特点的高超声速飞行器,提出了基于模糊自适应的高超飞行器高度控制方法,分别设计了高度和速度控制器.针对所设计的控制器,分析了气动干扰力矩、测量噪声、舵机干扰、气动参数不确定性和飞行器模型参数不确定性对飞行器高度控制和速度控制效果的影响,然后又分析了综合考虑以上干扰和不确定性对飞行器高度控制和速度控制效果的影响.仿真结果表明,对各种干扰和不确定性,所设计的控制器速度和高度控制有较好的跟踪性和鲁棒性,达到了满意的效果.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.     

A novel STAP method for the detection of fast air moving targets from high speed platform

Space-time adaptive processing (STAP) is an effective method for detecting moving target in airborne/spaceborne radar.However,the detection of fast air moving targets from high speed platform is challenged by the range walk of both the clutter and moving targets.It is well known that keystone formatting can be used to compensate for the range walk of multiple moving targets simultaneously without using the knowledge of the motion parameters.However,in the presence of serious Doppler ambiguity of fast air moving targets,distribution of the clutter will be affected by the keystone formatting matched to the ambiguity number of targets,and as a result the STAP performance will degrade.In this paper,a novel STAP method is proposed for the detection of fast air moving targets from high speed platform,which can deal with the range walk of both clutter and targets.Effectiveness of the new method is verified via simulation examples.     

Convex relaxation for a 3D spatiotemporal segmentation model using the primal-dual method

A method based on 3D videos is proposed for multi-target segmentation and tracking with a moving viewing system. A spatiotemporal energy functional is built up to perform motion segmentation and estimation simultaneously. To overcome the limitation of the local minimum problem with the level set method, a convex relaxation method is applied to the 3D spatiotemporal segmentation model. The relaxed convex model is independent of the initial condition. A primal-dual algorithm is used to improve computational efficiency. Several indoor experiments show the validity of the proposed method.     

酸碱中和反应中pH值的单神经元自适应控制研究

基于酸碱中和反应过程中pH值变化的动态模型,设计单神经元自适应控制器,解决化工生产过程中pH值的PID控制所存在的调节时间长、超调量大和系统抗干扰性差的问题。在相同条件下与PID控制器进行对比实验,实验结果表明单神经元自适应控制器明显改善pH值过程控制系统的动态性能,该控制系统具有较强的自适应性与鲁棒性。     

多特征自适应融合的粒子滤波跟踪算法

针对跟踪过程中目标形态不断变化或部分遮挡导致鲁棒性差的问题,提出一种基于多特征自适应融合的粒子滤波跟踪算法.该算法从视觉特征集中选取了描述能力强的2种特征,并将其按照与目标模型的多尺度相似度进行线性融合;为了减小跟踪漂移,通过计算当前目标模型与初始目标模型的多尺度相似度自适应地更新目标模型.大量仿真实验结果表明,文中算法可以鲁棒地跟踪到部分遮挡和形态变化的运动目标.