Search

The time optimal pursuit-evasion-capture (PEC) game problem for two spacecraft with continuous constant thrust is studied, which is a typical and considerable game scenario in practice. Progressive Shooting Method (PSM) is proposed to solve the PEC game in this paper. The method solves the problem in two stages. First-shooting settles a simplified problem by substituting CW dynamics to simple dynamics, while second-shooting settles the original problem with the results of first-shooting. For first-shooting, an analytic initial guess construction method based on prior information is proposed, in which vague adjoint variables are expressed by quantities with clear physical meanings. Through qualitative analysis for the optimal trajectory, the quantities are approximately estimated and then analytic expressions of an initial guess are constructed. The proposed method provides an instructive way to deal with the difficulty that an initial guess is hard to provide for an optimal control problem based on indirect-method. Numerical results show that a PEC game can be solved by the proposed method with well convergence and high computational efficiency. [ABSTRACT FROM AUTHOR]

For autonomous spacecraft close proximity under environments containing multiple obstacles and complicated constraints, incrementally rapid planning approaches stemming from sampling-based methods are investigated in this paper. Exploring planners are separately developed for the impulsive maneuvered translation and the piecewise constant controlled rotation, which, however, is constrained by the pointing limits coupling with relative positions during the proximity. Using a cost-informed parent-connecting strategy originating from dynamic programming as well as a sweeping growth fashion balanced between tree-based and graph-based methods, an asymptotically optimal unidirectional exploration method is proposed to search energy-efficient translational trajectory without collision. As for the rotation planning, the pointing constraints are taken as virtual obstacles in the state-space augmented with time horizon planned by the translation and, accordingly, a bidirectional exploration method is developed to generate constraint-satisfied slew paths with fast convergence rate. Numerical experiments indicate that the proposed sampling-based methods can rapidly return asymptotic optimal translation trajectory and rotation path satisfying collision avoidance and sensor field-of-view constraints. [ABSTRACT FROM AUTHOR]

Data-driven fault diagnosis, known to be simple and convenient, is more suitable for diagnosing the complicated spacecraft systems, e.g. the satellite power system. Nevertheless, it is difficult to extract the rules for diagnosing from unlabeled data. In this paper, a clustering approach based on neighborhood relationship and spatial grid partition is proposed to compensate for the above deficiency. In order to deal with the data-driven fault diagnosis issue, a diagnostic strategy is designed, which is a combination of the proposed clustering method and the entropy weight. Finally, multiple experiments, consisting of the artificial data clustering, comparison experiments on satellite data mining, and a case of fault diagnosis on satellite power system, are carried out to illustrate the versatility and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of mixed H∞ and passive control for flexible spacecrafts subject to nonuniform sampling and time-varying delay in the input channel. An impulsive observer-based controller is introduced and the resulting closed-loop system is a hybrid system consisting of a continuous time-delay subsystem and an impulsive differential subsystem. As a first result, we derive a generalized bounded real lemma (GBRL), that is, a generalized H∞ performance criterion, for the impulsive differential subsystem by constructing a time-varying Lyapunov functional. Then, on the basis of this GBRL and utilizing the Lyapunov–Krasovskii approach, a sufficient condition is derived to asymptotically stabilize the closed-loop system and simultaneously guarantee a prescribed mixed H∞ and passivity performance index. A design method is proposed for the desired controller, which can be readily constructed by solving a convex optimization problem with linear matrix inequalities (LMIs) constraints. Finally, numerical experiments are provided to support the theoretical results, and comparisons with former approaches are also discussed. [ABSTRACT FROM AUTHOR]

The stability and H ∞ performance analysis of a class of impulsive differential systems are addressed by using a two-point boundary value problem method. For convenience of computation, a sufficient and necessary condition for the existence of a solution to the two-point boundary value problem is expressed using a set of linear matrix inequalities. As an application example, we apply the suggested method to deal with the sampled-data H ∞ filtering problem. A numerical example of a mass–spring system is used to verify the effectiveness of the theoretical result. [ABSTRACT FROM AUTHOR]