Guaranteed performance based adaptive attitude tracking of spacecraft with control constraints

The guaranteed performance control problem of spacecraft attitude tracking with control constraint, disturbance and time-varying inertia parameters is investigated. A new saturation function is designed to satisfy different magnitude constraints by introducing a piecewise smooth asymmetric Gauss error function. Based on the mean-value theorem, the constrained problem is transformed into an unconstrained control design subject to an unknown bounded coefficient matrix. To satisfy the constraints by performance functions, a tracking error constrained control is developed based on a hyperbolic arc-tangent asymmetric barrier Lyapunov function (BLF). In the backstepping framework, an adaptive robust control law is proposed by employing a smooth robust term simultaneously counteracting the parametric and non-parametric uncertainties, where the unknown coefficient matrix resulting from the control constraint is compensated by a Nussbaum function matrix. Rigorous stability analysis indicates that the proposed control law realizes the asymptotically tracking of spacecraft attitude and that the tracking error remains in a prescribed set which implies the achievement of the guaranteed transient performance. Numerical simulations validate the proposed theoretical results.     

时延遥操作系统的非对称双通道波变量补偿法

为保证遥操作系统在时延条件下的稳定性,以及减少传统波变量方法的跟踪误差,提出一种非对称双通道波变量补偿法。该方法在前向通道波变量补偿法的基础上,采用能量整定器对反向通道的波变量进行补偿。通过调节波阻抗、滤波器和能量整定器的相关参数可以充分保证遥操作系统的稳定性和跟踪性能。实验结果表明该方法在保证时延遥操作系统稳定性的基础上,速度跟踪平均误差比传统波变量法减少70%以上,力跟踪平均误差比前向通道波变量补偿法减少60%以上。为了比较不同时延下本方法的效果,设计时延分别为3s和0.6s的2种实验。结果表明本方法在不同时延条件下均可以取得较好的效果。     

基于浸入与不变理论的航天器姿态跟踪自适应控制

针对惯性参数不确定的航天器姿态跟踪控制问题，基于浸入与不变（I&I）方法设计出了一种新的姿态跟踪控制器。研究结果表明，传统的浸入与不变方法运用到姿态跟踪模型，存在参数回归矩阵不可积进而导致偏微分方程无解析解的问题。针对该问题，提出了一种对回归矩阵改造使其满足可积条件的方法，通过动态放缩技术消除了回归矩阵改造前后的差异对闭环系统稳定性的影响，设计出了一种新的航天器姿态跟踪自适应控制器。通过李雅普诺夫稳定性分析方法证明了所设计的控制器能够保证闭环系统的全局渐近稳定性。相对于已有的基于动态放缩法的浸入与不变控制器，设计了一种全新的缩放因子，使得控制器的执行不需要缩放因子的信息，并且也不需要惯量矩阵的先验信息。最后，仿真对比实验进一步验证了所设计控制器的有效性和优越性。     

A novel strong tracking cubature Kalman filter and its application in maneuvering target tracking

The fading factor exerts a significant role in the strong tracking idea. However, traditional fading factor introduction method hinders the accuracy and robustness advantages of current strong-tracking-based nonlinear filtering algorithms such as Cubature Kalman Filter (CKF) since traditional fading factor introduction method only considers the first-order Taylor expansion. To this end, a new fading factor idea is suggested and introduced into the strong tracking CKF method. The new fading factor introduction method expanded the number of fading factors from one to two with reselected introduction positions. The relationship between the two fading factors as well as the general calculation method can be derived based on Taylor expansion. Obvious superiority of the newly suggested fading factor introduction method is demonstrated according to different nonlinearity of the measurement function. Equivalent calculation method can also be established while applied to CKF. Theoretical analysis shows that the strong tracking CKF can extract the third-order term information from the residual and thus realize second-order accuracy. After optimizing the strong tracking algorithm process, a Fast Strong Tracking CKF (FSTCKF) is finally established. Two simulation examples show that the novel FSTCKF improves the robustness of traditional CKF while minimizing the algorithm time complexity under various conditions.     

基于跟瞄和加表PI滤波近程相对导航方法

针对由于加速度计存在漂移和目标星加速度未知,基于C-W(Clohessey-Whiltshire)方程递推的近程相对导航无法长时间使用的问题,提出了一种基于跟瞄相对测量信息修正相对位置/相对速度误差和估计加表漂移的方法,并给出了比例积分(PI)滤波近程相对导航算法。最后,进行了工程应用方式分析和仿真验证。相对位置误差估计精度优于50 m。仿真结果表明:该方法既能确保相对位置和相对速度输出的连续性,又可抑制跟瞄观测噪声并消除长时间积分累积误差。基于PI滤波的近程相对导航方法计算简单,易于工程实现,且已通过在轨考核验证。     

Performance limitations in trajectory tracking control for air-breathing hypersonic vehicles

An integrated approach that considers the performance limitations of tracking control systems for air-breathing hypersonic vehicles is proposed. First, a set of ascent trajectories is obtained as candidates for tracking control through a trajectory design method that considers the available acceleration. Second, the basic theory of performance limitations, which is adopted to calculate the limits on control performance through the trajectory, is integrated. The open-loop dynamics of air-breathing hypersonic vehicles is responsible for these limits on the control system. Comprehensive specifications on stability, tracking accuracy, and robustness are derived, and the flight envelope with constraints and control specifications is identified. Simulation results suggest that trajectory design should consider restrictions on control performance to obtain reliable solutions.     

A Poisson multi-Bernoulli mixture filter with spawning based on Kullback–Leibler divergence minimization

In the classical form, the Poisson Multi-Bernoulli Mixture (PMBM) filter uses a PMBM density to describe target birth, surviving, and death, which does not model the appearance of spawned targets. Although such a model can handle target birth, surviving, and death well, its performance may degrade when target spawning arises. The reason for this is that the original PMBM filter treats the spawned targets as birth targets, ignoring the surviving targets’ information. In this paper, we propose a Kullback–Leibler Divergence (KLD) minimization based derivation for the PMBM prediction step, including target spawning, in which the spawned targets are modeled using a Poisson Point Process (PPP). Furthermore, to improve the computational efficiency, three approximations are used to implement the proposed algorithm, such as the Variational Multi-Bernoulli (VMB) filter, the Measurement-Oriented marginal MeMBer/Poisson (MOMB/P) filter, and the Track-Oriented marginal MeMBer/Poisson (TOMB/P) filter. Finally, simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.     

水下机器人路径控制与仿真

研究了水下机器人的路径跟踪问题.首先考虑重力、浮力、推力、水动力以及附加质量的影响,建立了6自由度水下机器人的动力学模型.在此基础上设计了非线性控制系统,包括一个内控制回路和一个外控制回路.内控制回路根据机器人动力学模型引入非线性补偿,使得经内控制回路作用后的机器人化为一个解耦的线性定常系统,外控制回路采用比例微分(PD)控制,根据机器人实际轨迹与期望轨迹间的偏差进行负反馈控制.最后通过MATLAB对水下机器人追踪水面目标和跟踪空间螺旋线进行仿真,并给出了仿真曲线,从仿真结果可以看出,利用该方法可以使水下机器人具有较强的抗干扰能力,能够较好地实现对时变理论轨迹的跟踪.     

A novel variable structure multi-model approach based on error-ambiguity decomposition

Model Set Adaptation (MSA) plays a key role in the Variable Structure Multi-Model tracking approach (VSMM). In this paper, the Error-Ambiguity Decomposition (EAD) principle is adopted to derive the EAD-MSA criterion that is optimal in the sense of minimizing the square error between the estimate and the truth. Consequently, the EAD Variable Structure first-order General Pseudo Bayesian (EAD-VSGPB1) algorithm and the EAD Variable Structure Interacting Multiple Model (EAD-VSIMM) algorithm are constructed. The proposed algorithms are tested in two groups of maneuvering target tracking scenarios under different modes and observation error conditions. The simulation results demonstrate the effectiveness of the EAD-VSMM approach and show that, compared to some existing multi-model algorithms, the proposed EAD-VSMM algorithms achieve more robust and accurate tracking results.     

基于RBF网络的跟踪特性角对接收信号影响模型研究

在航天发射任务中,地面遥外测设备跟踪特性角（α角、β角）对接收信号质量的影响非常大,由于α角、β角影响接收信号的机理非常复杂,一直以来只进行定性分析.在研究RBF（Rradial Basis Function,径向基函数）网络的基础上,利用RBF网络建立跟踪α角、β角对接收信号的影响模型,并用已知样本数据对模型进行训练和验证,详细论证模型参数的选取方法,给出跟踪特性角对接收电平影响的量化分析和预测的一种方法.利用模型对某次发射任务设备的接收电平进行了预测,预测结果与实测结果基本相符,满足应用要求,对提高航天发射任务地面测控系统风险评估能力有重要意义.