Cui Pingyuan

Large angular autonomous attitude maneuver of deep spacecraft using pseudospectral method

An autonomous large angular slew of deep spacecraft is studied, which is a key factor in the development of future spacecraft autonomous platform. The objective is to minimize some performance index and rotate the spacecraft to a desired attitude while subject to dynamic and geometric constraints. The investigated literature did not handle this problem very well either in performance or constraints consideration. In this paper, we propose a new approach based on pseudospectral method for autonomous attitude control, not only satisfies the nonconvex constraints but also optimizes performance. We approach this by two stages: (1) get the feasible path using RRT in Rodrigues space and (2) transform the optimal control problem to a nonlinear planning problem (NLP) utilizing Pseudospectral method. Finally, attitude path is obtained by solving the NLP with an initial value from (1). Simulation example is presented and discussed.

RHC‐based attitude control of spacecraft under geometric constraints

Purpose – The purpose of this paper is to propose an attitude control algorithm for spacecraft with geometric constraints.Design/methodology/approach – The geometric constraint is reformulated as a quadratic form when quaternion is used as attitude parameter, then the constraint is proved to be nonconvex and is further transformed to a convex one. By designing a new constraint formulation to satisfy the real constraint in the predictive horizon, the attitude control problem is reshaped to a convex planning problem which is based on receding horizon control.Findings – The proposed algorithm is more effective in handling geometric constraints than previous research which used single step planning control.Practical implications – With novel improvements to current methods for steering spacecraft from one attitude to another with geometric constraints, great attitude maneuver path can be achieved to protect instruments and meanwhile satisfy mission requirements.Originality/value – The attitude control algorit...

A reliable algorithm of rock detection and avoidance for safe spacecraft landing

A reliable algorithm of rock detection and avoidance for soft landing based on CCD landing camera is presented. Firstly, the image of landing zone is fast processed using multi-resolution analysis technique. The rocks of landing zone are detected reliably on the basis of lighting character. Secondly, the rocks detected are recognized and indexed in terms of unsupervised clustering algorithm. The topological diagram of rocks distributed on the landing zone is designed. Thirdly, the true hazard area of the landing zone is computed by the height from laser altimeter and the inner parameters of landing camera. Then the safe landing site selected is demanded to satisfy the safe bound of lander and exploration task. Finally, the safe avoidance strategy of lander is generated, which guides and controls the lander to maneuver to the new and safe site. Craters on the asteroids surface are the most importance navigation landmarks on the phase of orbiting exploration.

Deep space moving target detection based on technology of image matching

A detection method of moving targets in deep space is researched based on technology of image registration. According to the characteristics of deep space image information, a SUSAN feature point extraction algorithm is modified to inhibit isolated noises which are similar to sidereal feature points, and it effectively eliminates isolated noises. The geometric constraint among stars in the star image settles a feature points matching algorithm. Finally, matching of two images by affine transformation and differential option locates the moving target. Trials show that this method realizes moving targets detect and search in deep space where detector is under the condition with various disturbances.

An algorithm of asteroid craters detection based on Gradient Vector Flow Snake model

A method of craters detection based on Gradient Vector Flow (GVF) and Snake model is presented in this paper. Firstly, the original edge map of craters is detected by Canny operator, and the concave boundaries and ruptures are allowed in the edge map. Then, the external force of, which is called GVF, is computed as a diffusion of gradient vectors of the edge map derived from the image in the process of locating craters boundaries by the traditional active snake model. The problem of former poor convergence of concave boundaries can be solved. At last, the original positions of iteration processing of Snake model are judged by dynamic clustering algorithm, which improve the convergence speed. Experiments on real images of asteroids surface including single crater and several craters are simulated. Results have shown that GVF-Snake model can locate not only the concave boundaries, but also the serious ruptures of edge image. The boundaries of craters can be detected wholly.

Multiple gravity-assisted trajectory optimization using a hybrid method

Global optimization methods have been increasing under consideration for complicated trajectory optimization problems. A hybrid optimization method combining the global optimal properties of genetic algorithms with the local optimal characteristic of sequential quadratic programming has been developed. The genetic algorithm initially searches the parameter space for candidate gravity-assisted planetary. The best parameter of the genetic algorithm is submitted as an initial parameter set to the sequential quadratic programming module for improvement. This hybrid optimization method was applied to optimize and design transfer trajectory of Cassini mission. The effectiveness of this method is demonstrated by the rapid solution of interplanetary trajectory problems that involve complex features such as multiple gravity assist consideration.