Loopy belief propagation based data association for extended target tracking

The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements. Recently, the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus. Different from the belief propagation based Extended Target tracking based on Belief Propagation (ET-BP) algorithm proposed in our previous work, a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper. The proposed formulation can be solved by the Loopy Belief Propagation (LBP) algorithm. Furthermore, the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy. Finally, experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency. Additionally, the convergence of the proposed algorithm is verified in the simulations.     

Finite-time relative orbit-attitude tracking control for multi-spacecraft with collision avoidance and changing network topologies

This paper addresses the relative position tracking and attitude synchronization control problem for spacecraft formation flying (SFF). Based on the derived relative coupled six-degree-of-freedom dynamics, a robust adaptive finite-time fast terminal sliding mode controller is proposed to achieve the desired formation in the presence of model uncertainties and external disturbances. It is shown that the designed controller is effective for changing information exchange topology making it robust to node failure. Then, the artificial potential function method is employed to generate collision avoidance schemes to modify the controller such that inter-agent collision avoidance can be ensured during the formation maneuver, which is critical for practical missions. The stability of the overall closed-loop system is proved by using Lyapunov theory. Finally, numerical examples for a given SFF scenario are presented to illustrate the performance of the controller.     

Adaptive fuzzy neural network control for a space manipulator in the presence of output constraints and input nonlinearities

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this paper, a novel adaptive fuzzy neural network (FNN) control scheme is proposed for the trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of output constraints and input nonlinearities. The parametric uncertainties and external disturbances are also taken into the consideration. First, a model-based controller is designed by using the barrier Lyapunov function (BLF) to prevent the position tracking errors from violating the predefined output constraints. Then, an adaptive FNN controller is designed by using two FNNs to compensate for the lumped uncertainties and input nonlinearities, respectively. Rigorous theoretical analysis for the semiglobal uniform ultimate boundedness of the whole closed-loop system is provided. The proposed adaptive FNN controller can guarantee the position and velocity tracking errors converge to the small neighborhoods about zero, while ensuring the position tracking errors within the output constraints even in the presence of input nonlinearities. To the best of the authors’ knowledge, there are relatively few existing controllers can achieve such excellent control performance in the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control scheme.     

空间站柔性太阳电池翼对日跟踪控制

空间站柔性太阳电池翼高稳定对日跟踪驱动控制,对于保障空间站长期在轨能源安全和平稳运行具有重要意义。在推导柔性太阳电池翼动力学模型、柔性体模态分析和截断、Alpha对日定向装置机电系统模型、非线性传动系统模型的基础上,对空间站柔性太阳电池翼对日跟踪控制系统进行设计。采用Heaviside五次样条变速规划、位置和速度两级闭环、速度环陷阱滤波器柔性振动抑制的组合方案,实现空间站柔性太阳电池翼高稳定驱动控制。通过对典型工况的仿真校核,验证所设计的控制方案可实现跟踪精度优于0.3°、速度偏差±0.005(°)/s、稳定度优于7%@0.065(°)/s的性能指标。同时,Alpha对日定向装置的启动和变速过程中驱动力矩不大于30 N·m,稳速运行期间驱动力矩不大于5 N·m。各项性能指标要好于国际空间站Alpha对日定向装置,满足使用要求。     

Constrained adaptive fault-tolerant attitude tracking control of rigid spacecraft

A saturated fault-tolerant attitude tracking controller for disturbed rigid spacecraft is derived using nonlinear state feedback control method. The proposed controller achieves the constraints of control inputs by directly using the bounded function instead of the traditional saturation compensator technique, and the active tolerance to the partial loss of actuator effectiveness is also achieved by directly using the known bounds of the actuator faults in the controller. Specifically, compared with the traditional saturated control methods, a continuously bounded nonlinear function in the proposed controller is used to guarantee that the actuator outputs are smoothly bounded under the prescribed constraints. Based on some properties of the attitude tracking dynamics, the proposed controller can ensure the attitude tracking errors converge to small neighborhoods of zero via stability analysis in the Lyapunov framework. Simulation results are presented to illustrate the effectiveness of the control scheme.     

民航客机最佳机翼面积的优化方法

分析了民航客机燃油效率的影响因素,将气动阻力进行分解,推导出了以巡航效率为优化目标的最佳机翼优化方法。算例表明,无论是在飞机的方案设计阶段,还是在详细设计阶段,方法都是适用的。方法不仅可用于最佳机翼面积的优化工作,在详细设计阶段,还可用于检验飞机的气动优化设计是否偏离飞机的优化目标,以及检验飞机的最佳巡航航程指标是否与最佳燃油效率匹配。     

直-X直升机旋翼动平衡检查调整方法研究

通过对几十架直-X直升机旋翼动平衡检查调整的总结,结合维护手册和实际经验,提出了该型直升机旋翼动平衡检查调整方法,并在实际应用中取得了很好的效果.     

MCMC-Particle-based group tracking of space objects within Bayesian framework

With the intense increase in space objects, especially space debris, it is necessary to efficiently track and catalog the extensive dense clusters of space objects. As the main instrument for low earth orbit (LEO) space surveillance, ground-based radar system is usually limited by its resolution while tracking small space debris with high density. Thus, the obtained measurement information could have been seriously missed, which makes the traditional tracking method inefficient. To address this issue, we conceived the concept of group tracking. For group tracking, the overall tendency of the group objects is expected to be revealed, and the trajectories of individual objects are simultaneously reconstructed explicitly. According to model the interaction between the group center and individual trajectories using the Markov random field (MRF) within Bayesian framework, the objects’ number and individual trajectory can be estimated more accurately in the condition of high miss alarm probability. The Markov chain Monte Carlo (MCMC)-Particle algorithm was utilized for solving the Bayesian integral problem. Furthermore, we introduced the mechanism for describing the behaviors of groups merging and splitting, which can expand the single group tracking algorithm to track variable multiple groups. Finally, simulation of the group tracking of space objects was carried out to validate the efficiency of the proposed method.     

三角嵌铺粒子追踪算法的三维化扩展

针对连续帧三维流场粒子的匹配问题,对基于三角嵌铺的粒子追踪算法进行了三维化扩展并将其命名为3DT PTV。3DT PTV遵循从粒子样型匹配到粒子匹配的原则,即粒子匹配结果从粒子样型匹配结果中总结。首先通过自定义"粒子样型DT网格"实现了粒子样型匹配的参数无依赖性,使3DT PTV适用于粒子非均匀分布流场;其次通过自定义"样型唯一性标识向量"进行粒子样型匹配;最终通过"双向计算-概率择优"模块对样型匹配结果进行样本扩展并整合出粒子匹配。通过添加自定义干扰的JPIV人工流场对3DT PTV进行了检验。除了算法本身的简洁性,结果亦证明了3DT PTV处理粒子无匹配率较高的复杂流动的良好特性。     

高超声速飞行器DPIV内流阻力测量技术研究

为了研究吸气式高超声速飞行器的气动特性,提出一种新的内流阻力测量技术,即采用粒子图像测速技术和总压测量技术相结合,测量超燃发动机尾喷管流场速度矢量和皮托压力分布,间接获得内流出口处平均马赫数和内流出口处静压平均值,从而实现高超声速通气模型内流阻力测量。研究结果表明:粒子图像测速技术和总压测量技术相结合,成功地实现了内流阻力测量;试验获得的粒子图像,能够清楚地显示喷管出口位置内外流的分界面及边界层和边界层的尾迹;粒子图像测速试验获得的速度矢量场结果准确,精度高,能够提供远远超出传统测量技术所能提供的流场信息。 