1 |
PARTOVIBAKHSH M, LIU G J An adaptive unscented Kalman filtering approach for online estimation of model parameters and state-of-charge of lithium-ion batteries for autonomous mobile robots. IEEE Trans. on Automatic Control, 2014, 23 (1): 357- 363.
|
2 |
KIM C J, CHWA D Obstacle avoidance method for wheeled mobile robots using interval type-2 fuzzy neural network. IEEE Trans. on Fuzzy System, 2015, 23 (3): 677- 687.
doi: 10.1109/TFUZZ.2014.2321771
|
3 |
ZHANG D, CAI W J, XIE L H, et al Nonfragile distributed filtering for T-S fuzzy systems in sensor networks. IEEE Trans. on Fuzzy System, 2015, 23 (5): 1883- 1890.
doi: 10.1109/TFUZZ.2014.2367101
|
4 |
CHEN S, HO D W C, HUANG C Fault reconstruction and state estimator design for distributed sensor networks in multi target tracking. IEEE Trans. on Industrial Electronics, 2015, 62 (11): 7091- 7102.
doi: 10.1109/TIE.2015.2448685
|
5 |
DONG X W, YU B C, SHI Z Y, et al Time-varying formation control for unmanned aerial vehicles: theories and applications. IEEE Trans. on Control Systems Technology, 2015, 23 (1): 340- 348.
doi: 10.1109/TCST.2014.2314460
|
6 |
QI Y H, ZHOU S L, KANG Y H, et al Formation control for unmanned aerial vehicles with directed and switching topologies. International Journal of Aerospace Engineering, 2016, 2016, 7657452.
|
7 |
DANG Z H, ZHANG Y L Control design and analysis of an inner-formation flying system. IEEE Trans. on Aerospace and Electronic Systems, 2015, 51 (3): 1621- 1634.
doi: 10.1109/TAES.2014.130263
|
8 |
HUANG X L, ZHANG C, LU H Q, et al Adaptive reaching law based sliding mode control for electromagnetic formation flight with input saturation. Journal of the Franklin Institute, 2016, 353 (11): 2398- 2417.
doi: 10.1016/j.jfranklin.2016.04.004
|
9 |
WANG L, XI J X, HOU B, et al Limited-budget consensus design and analysis for multiagent systems with switching topologies and intermittent communications. IEEE/CAA Journal of Automatica Sinica, 2021, 8 (10): 1724- 1736.
doi: 10.1109/JAS.2021.1004000
|
10 |
ABBSL Y, MOOSAVIAN S A A, NOVINZADEH A B Formation control of aerial robots using virtual structure and new fuzzy based self-tuning synchronization. Transactions of the Institute Measurement and Control, 2017, 39 (12): 1906- 1919.
doi: 10.1177/0142331216649021
|
11 |
BALCH T, ARKIN R C Behavior-based formation control for multirobot teams. IEEE Trans. on Robot Automatic, 1998, 14 (6): 926- 939.
doi: 10.1109/70.736776
|
12 |
LIN J L, HWANG K S, WANG Y L, et al A simple scheme for formation control based on weighted behavior learning. IEEE Trans. on Neural Networks and Learning Systems, 2013, 25 (6): 1033- 1044.
|
13 |
LORIA A, DASDEMIR J, JARQUIN N A Leader-follower formation and tracking control of mobile robots along straight paths. IEEE Trans. on Control Systems Technology, 2015, 24 (2): 727- 732.
|
14 |
YANG X J, LIAO L J, YANG Q, et al Limited-energy output formation for multiagent systems with intermittent interactions. Journal of the Franklin Institute, 2021, 358 (13): 6462- 6489.
doi: 10.1016/j.jfranklin.2021.06.009
|
15 |
LI J L, XI J X, HE M, et al Formation control for networked multiagent systems with a minimum energy constraint. Chinese Journal of Aeronautics, 2023, 36 (1): 342- 355.
doi: 10.1016/j.cja.2022.01.015
|
16 |
REN W Consensus strategies for cooperative control of vehicle formations. IET Control Theory Application, 2007, 1 (2): 505- 512.
doi: 10.1049/iet-cta:20050401
|
17 |
ANDERSSON M, WALLANDER J Kin selection and reciprocity in flight formation. Behavioral Ecology, 2004, 15 (1): 158- 162.
doi: 10.1093/beheco/arg109
|
18 |
REN W, SORENSEN N Distributed coordination architecture for multirobot formation control. Robotics and Autonomous Systems, 2008, 56 (4): 324- 333.
doi: 10.1016/j.robot.2007.08.005
|
19 |
BRINON-ARRANZ L, SEURET A, CANUDAS-DE-WIT C Cooperative control design for time-varying formations of multi-agent systems. IEEE Trans. on Automatic Control, 2014, 59 (8): 2283- 2288.
doi: 10.1109/TAC.2014.2303213
|
20 |
YOO S J, KIM T H Distributed formation tracking of networked mobile robots under unknown slippage effects. Automatica, 2015, 54, 100- 106.
doi: 10.1016/j.automatica.2015.01.043
|
21 |
YAN C H, ZHANG W, LI X H, et al Observer-based time-varying formation tracking for one-sided Lipschitz nonlinear systems via adaptive protocol. International Journal of Control Automation and Systems, 2020, 18 (12): 2753- 2764.
|
22 |
LIU X F, XIE Y F, LI F B, et al Formation control of singular multiagent systems with switching topologies. International Journal of Robust Nonlinear Control, 2020, 30 (2): 652- 664.
doi: 10.1002/rnc.4789
|
23 |
XI J X, WANG L, ZHENG J F, et al Energy-constraint formation for multiagent systems with switching interaction topologies. IEEE Trans. on Circuits and Systems-I: Regular papers, 2020, 67 (7): 2442- 2454.
doi: 10.1109/TCSI.2020.2975383
|
24 |
YANG X, HUA C C, YAN J, et al Adaptive formation control of cooperative teleoperators with intermittent communications. IEEE Trans. on Cybernetics, 2018, 49 (7): 2514- 2523.
|
25 |
CHAI X F, LIU J, YU Y, et al Practical fixed-time event-triggered time-varying formation tracking control for disturbed multi-agent systems with continuous communication free. Unmanned Systems, 2021, 9 (1): 1- 12.
|
26 |
CAO Y C, REN W Optimal linear-consensus algorithms: an LQR perspective. IEEE Trans. on Systems, Man, and Cybernetics-Part B:Cybernetics, 2010, 40 (3): 819- 829.
doi: 10.1109/TSMCB.2009.2030495
|
27 |
ZHAO Y D, ZHANG W D Guaranteed cost consensus protocol design for linear multi-agent systems with sampled-data information: an input delay approach. ISA Transactions, 2017, 67, 87- 97.
doi: 10.1016/j.isatra.2016.12.003
|
28 |
WANG Z, HE M, ZHENG T, et al Guaranteed cost consensus for high-dimensional multi-agent systems with time-varying delays. IEEE/CAA Journal of Automatica Sinica, 2018, 5 (1): 181- 189.
doi: 10.1109/JAS.2017.7510430
|
29 |
YU J L, DONG X W, LI Q D, et al Robust guaranteed cost time-varying formation tracking for high-order multiagent systems with time-varying delays. IEEE Trans. on Systems Man Cybernetics: Systems, 2020, 50 (4): 1465- 1475.
doi: 10.1109/TSMC.2018.2883516
|
30 |
XI J X, WANG C, YANG X J, et al Limited-budget output consensus for descriptor multiagent systems with energy constraints. IEEE Trans. on Cybernetics, 2020, 50 (11): 4585- 4598.
doi: 10.1109/TCYB.2019.2963172
|
31 |
GODSIL C, ROYLE G. Algebraic graph theory. New York: Springer-Verlag, 2001.
|
32 |
YU W W, CAO J D, WANG J An LMI approach to global asymptotic stability of the delayed Cohen-Grossberg neural network via nonsmooth analysis. Neural Networks, 2007, 20 (7): 810- 818.
|
33 |
ANDERSON B D O, MOORE J B. Optimal control: linear quadratic methods. New York: Dover publications, 2007.
|
34 |
LIN Z Y, DING W, YAN G F, et al. Leader-follower formation via complex Laplacian. Automatica, 2013, 49(6): 1900−1906.
|
35 |
DONG X W, ZHOU Y, REN Z, et al Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying. IEEE Trans. on Industrial Electronics, 2017, 64 (6): 5014- 5024.
doi: 10.1109/TIE.2016.2593656
|
36 |
WANG J N, XIN M. Integrated optimal formation control of multiple unmanned aerial vehicles. IEEE Trans. on Control Systems Technology, 2013, 21(5): 1731−1744.
|
37 |
WANG J N, BI C Y, WANG D D, et al. Finite-time distributed event-triggered formation control for quadrotor UAVs with experimentation. ISA Transactions, 2022, 126: 585−596.
|