CANYVAL-C is a formation-flying mission that demonstrates a coronagraph utilizing two CubeSats. The coronagraph is a space telescope that blocks sunlight to examine the overcast regions around the sun. It is composed of optical and occult segments. Two spacecraft were aligned with respect to an inertial system to configure a virtual telescope using inertial alignment hold technology. The relative orbit control scenario for this mission involves rendezvous, differential air drag control, and inertial alignment holding. Orbit control algorithms and simple strategies that can be automatically constructed onboard have also been developed. For each maneuver, the control performance under the errors from navigation, attitude determination and control, and propulsion systems were assessed via Monte Carlo simulation, taking into account the hardware specifications and operations. In addition to the algorithm and strategy of this mission, the relative orbit control scenario was evaluated for its practicability using Monte Carlo simulations. The feasibility of this mission is ensured by a statistical analysis of the prospect of its success during its operation.

This paper presents a nonsingular fast terminal sliding mode-based adaptive smooth control methodology for a distributed space telescope demonstration mission. The distributed space telescope has a flexible focal length that corresponds to the relative position in the formation flying concept. The limited specification of a CubeSat generally restricts the performance of actuators – most critically the degrees of freedom of controlled motion. This investigation leads to the development of an adaptive smooth control methodology via nonsingular fast terminal sliding modes. The adaptive smooth control algorithm that was developed for a singleinput single-output system is adopted and extended to the relative orbit and attitude control systems of the distributed space telescope. The software simulation is conducted under a real mission, which means the real CubeSat structures, hardware specifications, and operational constraints. The proposed algorithm possesses only seven parameters that can be easily adjusted considering their physical meanings. Furthermore, the pre-designated error bounds are analytically derived, which enhances the applicability of the algorithm to real missions. The simulation compares the efficiency of the adaptive smooth nonsingular fast terminal sliding mode controller with the linear quadratic regulator and proportional derivative algorithms. The results verify that the adaptive smooth nonsingular fast terminal sliding mode control algorithm shows better control performance in the perspective of the alignment time and the fuel consumption for the distributed space telescope demonstration mission.