Connectivity Preservation and Obstacle Avoidance in Small Multi-Spacecraft Formation with Distributed Adaptive Tracking Control

This paper proposes an adaptive tracking control scheme for multi-spacecraft formation with inter-collision avoidance, obstacle dodging, and connectivity preservation. The proposed scheme is distributed, i.e., each spacecraft only needs to communicate with its neighbours. Both connectivity preservation and distributed networking are critical features for small spacecraft formation with limited computation and communication capacities. New artificial potential functions are defined to preserve the connectivity of neighbour spacecraft while avoiding their inter-collision as well as collision with obstacles. An adaptive sliding-mode controller is designed for reaching and maintaining the predetermined formation configuration while satisfying the safety assurance requirements, including inter-collision avoidance, obstacle dodging, and connectivity preservation. The stability of the controller is proven through the Lyapunov analysis, in the presence of gravitational, solar radiation pressure, and atmosphere drag perturbations and dynamic uncertainties. The performance of the control scheme is demonstrated through several comparative simulation studies.

[1]  Nicolas Jouandeau,et al.  A Survey and Analysis of Multi-Robot Coordination , 2013 .

[2]  Veysel Gazi,et al.  Swarm aggregations using artificial potentials and sliding-mode control , 2005, IEEE Transactions on Robotics.

[3]  Bruno Jouvencel,et al.  Coordinated Formation Control of Multiple Autonomous Underwater Vehicles for Pipeline Inspection , 2010 .

[4]  Guo-Ping Liu,et al.  A Survey on Formation Control of Small Satellites , 2018, Proceedings of the IEEE.

[5]  Youfeng Su,et al.  Leader-following rendezvous with connectivity preservation and disturbance rejection via internal model approach , 2015, Autom..

[6]  Steven P. Neeck,et al.  NASA-GSFC nano-satellite technology for Earth science missions , 2000 .

[7]  Hamid Reza Karimi,et al.  A Novel Finite-Time Control for Nonstrict Feedback Saturated Nonlinear Systems With Tracking Error Constraint , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[8]  C. Seubert.  Refrigerant-based propulsion system for small spacecraft , 2007 .

[9]  Jun Zhou,et al.  Distributed RISE control for spacecraft formation reconfiguration with collision avoidance , 2019, J. Frankl. Inst..

[10]  Fuat Cogun,et al.  Moving Shadow Detection in Video Using Cepstrum , 2013 .

[11]  M. Reza Emami,et al.  A multi-spacecraft formation approach to space debris surveillance , 2016 .

[12]  M Innocenti,et al.  Decentralized Control of a Swarm of unmanned Air Vehicles , 2007 .

[13]  Shin-ichiro Nishida,et al.  Space debris removal system using a small satellite , 2006 .

[14]  Riccardo Bevilacqua,et al.  Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft , 2011 .

[15]  Xiaoping Yun,et al.  Autonomous Distributed Control Algorithm for Multiple Spacecraft in Close Proximity Operations , 2007 .

[16]  Per Johan Nicklasson,et al.  Spacecraft formation reconfiguration with collision avoidance , 2011, Autom..

[17]  Shengyuan Xu,et al.  Flocking with connectivity preservation for disturbed nonlinear multi-agent systems by output feedback , 2018, Int. J. Control.

[18]  Yingmin Jia,et al.  Neural network-based distributed adaptive attitude synchronization control of spacecraft formation under modified fast terminal sliding mode , 2016, Neurocomputing.

[19]  Pu Zhang,et al.  Fixed-Wing UAV Formation Control Design With Collision Avoidance Based on an Improved Artificial Potential Field , 2018, IEEE Access.

[20]  Lorenzo Sabattini,et al.  Arbitrarily shaped formations of mobile robots: artificial potential fields and coordinate transformation , 2011, Auton. Robots.

[21]  Frank L. Lewis,et al.  Robust time‐varying formation control for multiple underwater vehicles subject to nonlinearities and uncertainties , 2019, International Journal of Robust and Nonlinear Control.

[22]  Mark W. Spong,et al.  Collision-Free Formation Control with Decentralized Connectivity Preservation for Nonholonomic-Wheeled Mobile Robots , 2015, IEEE Transactions on Control of Network Systems.

[23]  F.Y. Hadaegh,et al.  A survey of spacecraft formation flying guidance and control. Part II: control , 2004, Proceedings of the 2004 American Control Conference.

[24]  Magnus Egerstedt,et al.  Distributed Coordination Control of Multiagent Systems While Preserving Connectedness , 2007, IEEE Transactions on Robotics.

[25]  David Krejci,et al.  Space Propulsion Technology for Small Spacecraft , 2018, Proceedings of the IEEE.

[26]  Riccardo Bevilacqua,et al.  Survey on Guidance Navigation and Control Requirements for Spacecraft Formation-Flying Missions , 2017 .

[27]  Xiaoping Yun,et al.  Autonomous Distributed LQR/APF Control Algorithm for Multiple Small Spacecraft during Simultaneous Close Proximity Operations , 2007 .

[28]  Vinod Kumar,et al.  Multisatellite Formation Control for Remote Sensing Applications Using Artificial Potential Field and Adaptive Fuzzy Sliding Mode Control , 2015, IEEE Systems Journal.

[29]  Francisco R. Rubio,et al.  Formation Control of Autonomous Underwater Vehicles Subject to Communication Delays , 2014 .

[30]  Tieshan Li,et al.  Adaptive leader-following formation control with collision avoidance for a class of second-order nonlinear multi-agent systems , 2019, Neurocomputing.

[31]  Youmin Zhang,et al.  Tracking control of spacecraft formation flying with collision avoidance , 2015 .

[32]  Kangkang Sun,et al.  Event-Triggered Robust Fuzzy Adaptive Finite-Time Control of Nonlinear Systems With Prescribed Performance , 2020, IEEE Transactions on Fuzzy Systems.

[33]  Shuzhi Sam Ge,et al.  Formation Tracking Control of Multiagents in Constrained Space , 2016, IEEE Transactions on Control Systems Technology.

[34]  Huagang Liu,et al.  Distributed rigid formation control algorithm for multi-agent systems , 2012, Kybernetes.

[35]  Krishna Dev Kumar,et al.  Fault Tolerant Reconfigurable Satellite Formations Using Adaptive Variable Structure Techniques , 2010 .

[36]  Dong Qiao,et al.  Suboptimal artificial potential function sliding mode control for spacecraft rendezvous with obstacle avoidance , 2018 .

[37]  Saptarshi Bandyopadhyay,et al.  Information-Driven Systems Engineering Study of a Formation Flying Demonstration Mission using Six CubeSats , 2015 .

[38]  Shengyuan Xu,et al.  Adaptive finite-time flocking for uncertain nonlinear multi-agent systems with connectivity preservation , 2018, Neurocomputing.

[39]  Khashayar Khorasani,et al.  A distributed model predictive control (MPC) fault reconfiguration strategy for formation flying satellites , 2016, Int. J. Control.

[40]  Yang Zhou,et al.  Neural network-based adaptive second order sliding mode control of Lorentz-augmented spacecraft formation , 2017, Neurocomputing.

[41]  Yulin Zhang,et al.  Self-organizing control for satellite clusters using artificial potential function in terms of relative orbital elements , 2019, Aerospace Science and Technology.

[42]  Zhaowei Sun,et al.  Finite-time relative orbit-attitude tracking control for multi-spacecraft with collision avoidance and changing network topologies , 2019, Advances in Space Research.

[43]  S. Vadali,et al.  Formation Flying: Accommodating Nonlinearity and Eccentricity Perturbations , 2003 .

[44]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[45]  Zhang Ren,et al.  Practical time-varying output formation tracking for high-order multi-agent systems with collision avoidance, obstacle dodging and connectivity maintenance , 2019, J. Frankl. Inst..

[46]  Marco Lovera,et al.  A Predictive Approach to Formation Keeping for Constellations of Small Spacecraft in Elliptic Orbits , 2002 .

[47]  Eduardo Gamaliel Hernández-Martínez,et al.  Distance-based Formation Control Using Angular Information Between Robots , 2016, J. Intell. Robotic Syst..

[48]  Saptarshi Bandyopadhyay,et al.  Review of Formation Flying and Constellation Missions Using Nanosatellites , 2016 .

[49]  Nak Yong Ko,et al.  A formation and traction control design for multiple mobile robots , 2017 .

[50]  Jianliang Wang,et al.  Distributed Formation and Reconfiguration Control of VTOL UAVs , 2017, IEEE Transactions on Control Systems Technology.

[51]  Dimitra Panagou,et al.  A Distributed Feedback Motion Planning Protocol for Multiple Unicycle Agents of Different Classes , 2017, IEEE Transactions on Automatic Control.

[52]  Arindam Mondal,et al.  Trajectory Tracking by Multiple Agents in Formation With Collision Avoidance and Connectivity Assurance , 2018, IEEE Systems Journal.

[53]  Housheng Su,et al.  Flocking of multiple autonomous agents with preserved network connectivity and heterogeneous nonlinear dynamics , 2013, Neurocomputing.

[54]  Daero Lee,et al.  Asymptotic Tracking Control for Spacecraft Formation Flying with Decentralized Collision Avoidance , 2015 .

[55]  Manoranjan Sinha,et al.  Fault detection and recovery of spacecraft formation flying using nonlinear observer and reconfigurable controller , 2014 .

[56]  Jianbin Qiu,et al.  Fuzzy Adaptive Finite-Time Fault-Tolerant Control for Strict-Feedback Nonlinear Systems , 2020, IEEE Transactions on Fuzzy Systems.

[57]  Jonathan P. How,et al.  Spacecraft Formation Flying: Dynamics, Control and Navigation , 2009 .

[58]  Eduardo Aranda-Bricaire,et al.  Convergence and Collision Avoidance in Formation Control: A Survey of the Artificial Potential Functions Approach , 2011 .

[59]  Yi Dong,et al.  Flocking with connectivity preservation of multiple double integrator systems subject to external disturbances by a distributed control law , 2015, Autom..

[60]  Chuanjiang Li,et al.  Satellite affine formation flying with obstacle avoidance , 2019 .

[61]  David A. Spencer,et al.  Establishment and control of spacecraft formations using artificial potential functions , 2019, Acta Astronautica.

[62]  Holger Voos,et al.  Model predictive cooperative localization control of multiple UAVs using potential function sensor constraints , 2019, Auton. Robots.