Robust spline-line energy management guidance algorithm with multiple constraints and uncertainties for solid rocket ascending

For the solid rocket with depletion shutdown system, effective energy management is significant to meet terminal constraints by exhausting excess energy. Several traditional energy management algorithms cannot satisfy the altitude constraint and path constraints are not sufficiently considered. The velocity adjustment capability of these algorithms is limited and the uncertainties are not considered. Based on the on-line programming of velocity capability curve, Spline-Line Energy Management(SLE...     

考虑UAV性能约束的变速度自主避障算法研究

动态不确定环境下,为有效地提升UAV执行任务的安全性和可靠性,在UAV自主避障过程中考虑了自身的性能约束条件.在速度障碍圆弧法的基础上,考虑UAV的法向和纵向加速度约束范围,研究了速度障碍圆弧随速度矢量变化的规律,提出了一种考虑UAV性能约束的变速度自主避障算法.该算法在考虑自身性能约束条件下,为实现UAV对威胁障碍的避碰提供了更大的避碰裕度.最后,对考虑UAV性能约束的变速度自主避障算法进行了验证,仿真结果证明了算法的有效性和可行性.     

功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势，可以更加充分地利用频谱资源。设计了一种新的一体化波形，在实现通信符号传递的同时，利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出，其中以星座图上的范数误差衡量通信性能，以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际，在问题求解时同时考虑了波形总功率约束和波形恒模约束，并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。     

基于自适应通信拓扑的无人机集群弱路径约束下的分布式控制器设计

针对传统无人机集群飞行控制需要规划过多飞行路径的问题，设计一种结合线性二次型调节器(LQR)与机间防撞的分布式协同控制器，不需要为集群设计相对构型，只需给定一条满足无人机动力学约束的飞行路径，集群就可沿路径飞行。该控制器通过设计自适应通信拓扑来稳定加入机间防撞机制带来的抖振效应，并使集群具有良好可扩展性。仿真结果表明，所设计的分布式控制器可以实现规划一条路径下无人机集群无机间碰撞的稳定飞行。     

Measurement-driven Gauss-Hermite particle filter with soft spatiotemporal constraints for multi-optical theodolites target tracking

Multi-Optical Theodolite Tracking systems (MOTTs) can stealthily extract the target’s status information from bearings only through non-contact measurement. The constrained MOTTs are partially compatible, yet many existing research works and results are based on the known model, ignoring its discrimination with the target maneuvering behavior pattern. To compensate for these mismatches, this paper develops a Measurement-driven Gauss-Hermite Particle Filter (MGHPF), which elegantly fuses the spatiotemporal constraints and its soft form to perform MOTT missions. Specifically, the target dynamic model and tracking algorithm are based on the target behavior pattern with the adaptive turn rate, fully exploiting the spatial epipolar geometry characteristics for each intersection measurement by a minimax strategy. Then, the center of the feasible area is approximated via the analytic coordinate transformation, and the latent samples are updated via the deterministic Gauss-Hermite integral method with the target’s predictive turn rate. Simultaneously, the effects of truncation correction and compensation feedback from the current measurement and historical estimation data are adaptively incorporated into the PF’s importance distribution to cover the mixture likelihood. Besides, an effective causality-invariant updating rule is provided to estimate the parameters of these soft spatiotemporal constrained MOTTs with convergence guarantees. Simulated and measured results show good agreement; compared with the state-of-the-art Multi-Model Rao-Blackwell Particle Filter (MMRBPF), the proposed MGHPF improves the filtering accuracy by 7.4%-34.7% and significantly reduces the computational load.     

A new interpretable fault diagnosis method based on belief rule base and probability table

It is vital to establish an interpretable fault diagnosis model for critical equipment. Belief Rule Base (BRB) is an interpretable expert system gradually applied in fault diagnosis. However, the expert knowledge cannot be utilized to establish the initial BRB accurately if there are multiple referential grades in different fault features. In addition, the interpretability of BRB-based fault diagnosis is destroyed in the optimization process, which reflects in two aspects: deviation from the initial expert judgment and over-optimization of parameters. To solve these problems, a new interpretable fault diagnosis model based on BRB and probability table, called the BRB-P, is proposed in this paper. Compared with the traditional BRB, the BRB-P constructed by the probability table is more accurate. Then, the interpretability constraints, i.e., the credibility of expert knowledge, the penalty factor and the rule-activation factor, are inserted into the projection covariance matrix adaption evolution strategy to maintain the interpretability of BRB-P. A case study of the aerospace relay is conducted to verify the effectiveness of the proposed method.     

Topology optimization of turbine disk considering maximum stress prediction and constraints

For the stress-constrained topology optimization of a turbine disk under centrifugal loads, the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value. It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints. This paper proposes a new method for predicting the maximum stress to overcome the difficulty. In the process, a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements, a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements, two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements, and a linear stress penalty is further adopted to relax the stress field of the structure. The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk. An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress. Some key ingredients affecting the optimization results are discussed in detail. The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.     

Model predictive control for close-proximity maneuvering of spacecraft with adaptive convexification of collision avoidance constraints

This study investigated model predictive control (MPC) for close-proximity maneuvering of spacecraft. It is essential for a designed MPC to effectively handle collision avoidance between the servicer spacecraft and the client spacecraft, especially while the client is rotating. The rotating motion of the client leads to dynamic changes in the collision avoidance constraints, which increases the difficulty of optimizing the control input in the MPC framework. Therefore, this study presents a method to improve the performance and computational efficiency of MPC for rendezvous and docking with a nonrotating or rotating client. An ellipsoid is adopted to model the client’s keep-out zone (KOZ). Given the spherical KOZ of the servicer, an expanded ellipsoid is introduced to describe the KOZ for the center of mass of the servicer and modeled as a nonlinear constraint. The linearization method for reference points located at the expanded ellipsoid is adopted to convexify the nonlinear constraints. The reference points are adaptively determined according to the positions of the servicer, client, and expanded ellipsoidal KOZ. The resulting hyperplanes are then used to describe the collision avoidance constraints. By utilizing the aforementioned strategies, combined with the calculated reference points, an adaptive convex programming algorithm suitable for real-time implementation of MPC is derived. The performance of the proposed method is demonstrated through numerical simulations.     

状态/输入约束下飞-推一体化的保性能安全控制

基于飞行-推力一体化思想提出了一种针对搭载超燃冲压发动机的吸气式高超声速飞行器速度通道的状态/输入约束自适应鲁棒保性能安全控制方案。首先根据超燃冲压发动机的机理分析与计算流体动力模型数据，建立了安全子系统与性能子系统面向控制的仿射非线性模型。之后基于障碍Lyapunov理论与动态面设计方法设计了一套安全子系统状态约束控制器，从理论上保证了飞行器在跟踪指令的全过程中，发动机相关状态不会触碰安全边界，并结合自适应技术与辅助系统提高了该控制系统的鲁棒性。针对性能子系统设计了一套鲁棒自抗扰控制器，达到“保证安全的前提下不折损性能”的目的。仿真结果表明所设计的控制系统可以在保障安全的同时达到预想的性能，并显著放宽了超燃冲压发动机对飞行器飞行姿态的约束，保证了高超声速飞行器的机动灵活性。     

大气层内固体火箭多约束鲁棒三维能量管理制导

针对固体运载火箭大范围精确调节终端约束的要求，提出一种新型的大气层内鲁棒三维能量管理制导方法，通过在线规划侧向速度能力曲线消耗剩余发动机能量。将终端约束表示为关于攻角和速度能力曲线参数的方程组，将闭环制导问题转化为方程组的求解。针对飞行过程中的动压、过载，以及控制变化率等过程约束，构造了攻角和速度能力曲线的可行边界。针对气动系数和发动机参数的不确定性，采用容积卡尔曼滤波器对不确定性进行辨识。仿真结果表明，与模型预测静态规划算法和改进粒子群算法相比，本算法的终端速度调节范围、鲁棒性以及计算效率大幅度提高。