Novel moderate transformation of fuzzy membership function into basic belief assignment

In information fusion, the uncertain information from different sources might be modeled with different theoretical frameworks. When one needs to fuse the uncertain information represented by different uncertainty theories, constructing the transformation between different frameworks is crucial. Various transformations of a Fuzzy Membership Function (FMF) into a Basic Belief Assignment (BBA) have been proposed, where the transformations based on uncertainty maximization and minimization can determine the BBA without preselecting the focal elements. However, these two transformations that based on uncertainty optimization emphasize the extreme cases of uncertainty. To avoid extreme attitudinal bias, a trade-off or moderate BBA with the uncertainty degree between the minimal and maximal ones is more preferred. In this paper, two moderate transformations of an FMF into a trade-off BBA are proposed. One is the weighted average based transformation and the other is the optimization-based transformation with weighting mechanism, where the weighting factor can be user-specified or determined with some prior information. The rationality and effectiveness of our transformations are verified through numerical examples and classification examples.     

Warhead power assessment based on double hierarchy hesitant fuzzy linguistic term sets theory and gained and lost dominance score method

Warhead power assessment of the anti-ship missile plays a vital role in determining the optimal design of missile, thus having important strategic research significance. However, in the assessment process, expert’s judgement will directly affect the assessment accuracy. In addition,there are many criteria involved in the missile design alternatives. Some criteria with poor performance may be compensated by other criteria with excellent performance, and then it is impossible to find the truly opt...     

Adaptive feedback control of stability in an axial compressor with circumferential inlet distortion

The adaptive feedback control of stability with circumferential inlet distortion has been experimentally investigated in a low-speed, axial compressor. The flat-baffles with different span heights are used to simulate different distorted inflow cases. Compared with auto-correlation and root-mean-square analysis, cross-correlation analysis used to predict early stall warning does not depend on the distortion position. Hence, the cross-correlation coefficient was used to monitor the stable status of the compressor and provide the feedback signal in the active control strategy when suffering from different distortions. Based on the stall margin improvement of tip air injection obtained under different distorted inflow cases and the sensitivity analysis of cross-correlation coefficients to injected momentum ratios, tip air injection was adopted as the actuator for adaptive feedback control. The digital signal processing controller was designed and applied to achieve adaptive feedback control in distorted inflow conditions. The results show that the adaptive feedback control of air injection nearly achieves the same stall margin improvement as steady air injection under different distortion intensities with a reduced injection mass flow. Thus, the proposed adaptive feedback control method is ideal for the engine operation with circumferential distorted inflow, which frequently occurs in flight.     

A serialized civil aircraft R&D cost estimation model considering commonality based on BP algorithm

The common design of serial civil aircraft, an important strategy of modern civil aircraft research and develop-ment, minimizes the whole life cycle cost of civil aircraft through asset reuse and resource sharing. However, the existing estimating model for the R&D cost of civil aircraft ignores the effects of common design, so the value estimated by estimating derivative models is significantly inconsistent with the actual one. To solve this problem, a novel assessment method for civil aircr...     

Optimal trajectory design accounting for the stabilization of linear time-varying error dynamics

This study is dedicated to the development of a direct optimal control-based algorithm for trajectory optimization problems that accounts for the closed-loop stability of the trajectory tracking error dynamics already during the optimization. Consequently, the trajectory is designed such that the Linear Time-Varying(LTV) dynamic system, describing the controller’s error dynamics, is stable, while additionally the desired optimality criterion is optimized and all enforced constraints on the traje...     

基于模糊核均值聚类优化的光流测速方法CSCD

光流算法作为一种载体速度测量方法,易受光照变化、物体相对移动影响,最终导致速度信息获取不准确。为了提高载体运动速度解算精度,提出了一种基于模糊核均值聚类算法优化的金字塔Lucas-Kanade光流测速方法(FKCM-金字塔LK)。该方法首先通过金字塔LK光流算法得到稀疏光流,然后使用模糊核均值聚类算法对稀疏光流数据进行聚类处理,最终建立光流与实验平台运动参数之间的关系,并得到准确的速度信息。实验结果表明,提出的基于模糊核均值聚类算法优化的金字塔LK光流测速方法不仅可以有效地减少物体相对移动对光流测速的影响,而且与现有其他光流测速方法相比,速度测量精度得到显著提高。     

基于模糊神经网络的智能PID控制算法

舵机控制系统存在响应速度慢、抗干扰能力差、系统参数不易整定、现有控制技术与设计方法的局限性等问题,这些问题影响了舵机的性能。为了提高制导火箭弹舵机伺服控制系统的性能,文章从舵机智能控制技术出发,研究了舵机的智能控制算法和Simulink系统仿真模型,采用模糊神经网络PID控制器来提高舵机的稳定性。仿真结果表明,模糊神经网络相比其他控制器进一步提升了舵机控制系统的控制效果。     

动态负调约束下固体冲压发动机燃气流量控制算法研究

变流量固体冲压发动机工作过程中，常采用控制燃气发生器压强的方式调节燃气生成量，在跟踪变化压强指令过程中，流量会产生明显的负调现象，严重影响发动机系统的安全性和可靠性。为 解决这一问题，本文以具有高度非线性、强时变特性的燃气发生器系统为对象，构建了基于粒子群算法的流量调节自适应PI控制器，并给出一种利用自适应微分跟踪器对期望控制指令进行“整形”的负调改善算法；首先，结合负调发生、终止判据，综合考量系统流量安全裕度，负调发生方向，构建了适配于动态负调约束的自适应跟踪微分器（TD），克服了传统跟踪微分器在负调抑制过程中控制精度不高，指向性不强等缺陷；进一步，开展了多工况下的负调抑制算法仿真校验，结果表明：所设计自适应控制算法具备良好的燃气流量控制能力，可实现在基本不改变响应时间情况下，将最大负调量削减56.6%的控制效果，展现出良好的工程应用前景。     

基于新型变速趋近律的永磁同步电机滑模控制

为了改善永磁同步电机(PMSM)调速系统的动态品质,提出了一种基于变速趋近律方法的PMSM滑模速度控制策略。为了提高传统指数趋近律的收敛速度和消除系统抖阵现象的影响,在传统指数趋近律的基础上提出了一种新型变速趋近律方法,并应用该方法设计了一种PMSM调速系统的滑模速度控制器。通过仿真和试验结果对比分析,证明该算法不仅改善了系统的鲁棒性能,同时改善了系统的动态响应速度。