In this study, consensus tracking control is considered for a class of nonlinear second-order multi-agent systems in an undirected communication topology subject to input magnitude and rate constraints (MRCs). Initially, the control inputs are designed directly using the smooth hyperbolic tangent function. Subsequently, some auxiliary signals are developed to guarantee input rate constraints simultaneously. By employing the backstepping method, the proposed control scheme can ensure uniform ultimate boundedness of the closed-loop system, and the consensus tracking error of each agent can converge to a small neighborhood near zero. Finally, the single-link robot manipulator multi-agent system model is used to perform numerical simulations to demonstrate the control effect further.
BenderFGomes da SilvaJJr (2012) Output feedback controller design for systems with amplitude and rate control constraints. Asian Journal of Control14(4): 1113–1117.
2.
BöhnleinDSchweigerKTumaA (2011) Multi-agent-based transport planning in the newspaper industry. International Journal of Production Economics131(1): 146–157.
3.
ChengZZhangHTFanMC, et al. (2014) Distributed consensus of multi-agent systems with input constraints: A model predictive control approach. IEEE Transactions on Circuits and Systems I: Regular Papers62(3): 825–834.
4.
FischerTGehringH (2005) Planning vehicle transhipment in a seaport automobile terminal using a multi-agent system. European Journal of Operational Research166(3): 726–740.
5.
FuJLvYHuangT (2019) Distributed anti-windup approach for consensus tracking of second-order multi-agent systems with input saturation. Systems & Control Letters130: 1–6.
6.
GaoYLiuBYuJ, et al. (2014) Consensus of first-order multi-agent systems with intermittent interaction. Neurocomputing129: 273–278.
7.
GuXJiaTNiuY (2020) Consensus tracking for multi-agent systems subject to channel fading: A sliding mode control method. International Journal of Systems Science51(14): 2703–2711.
8.
HuiYChiRHuangB, et al. (2020) Observer-based sampled-data model-free adaptive control for continuous-time nonlinear nonaffine systems with input rate constraints. IEEE Transactions on Systems, Man, and Cybernetics: Systems51(12): 7813–7822.
9.
JiNLiuZLiuJ, et al. (2018) Vibration control for a nonlinear three-dimensional Euler-Bernoulli beam under input magnitude and rate constraints. Nonlinear Dynamics91(4): 2551–2570.
10.
KimBAhnH (2014) Distributed coordination and control for a freeway traffic network using consensus algorithms. IEEE Systems Journal10(1): 162–168.
11.
LiuBHouMNiJ, et al. (2020b) Asymmetric integral barrier Lyapunov function-based adaptive tracking control considering full-state with input magnitude and rate constraint. Journal of the Franklin Institute357(14): 9709–9732.
12.
LiuZWangXWangF, et al. (2020a) Fault-tolerant consensus control with control allocation in a leader-following multi-agent system. Journal of the Franklin Institute357(14): 9614–9632.
13.
LuWZongCLiJ, et al. (2022) Bipartite consensus-based formation control of high-order multi-robot systems with time-varying delays. Transactions of the Institute of Measurement and Control44(6): 1297–1308.
14.
MiaoGXuSZouY (2013) Consentability for high-order multi-agent systems under noise environment and time delays. Journal of the Franklin Institute350(2): 244–257.
15.
MuBZhangKShiY (2017) Integral sliding mode flight controller design for a quadrotor and the application in a heterogeneous multi-agent system. IEEE Transactions on Industrial Electronics64(12): 9389–9398.
16.
OtaJ (2006) Multi-agent robot systems as distributed autonomous systems. Advanced Engineering Informatics20(1): 59–70.
17.
PolycarpouMIoannouP (1996) A robust adaptive nonlinear control design. Automatica32(3): 423–427.
18.
ShiLXieD (2020) Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights. Transactions of the Institute of Measurement and Control42(16): 3156–3167.
19.
TaQMCheahCC (2020) Multi-agent control for stochastic optical manipulation systems. IEEE/ASME Transactions on Mechatronics25(4): 1971–1979.
20.
WangBChenWZhangB (2019) Semi-global robust tracking consensus for multi-agent uncertain systems with input saturation via metamorphic low-gain feedback. Automatica103: 363–373.
21.
WangBWangJZhangB, et al. (2016) Global cooperative control framework for multiagent systems subject to actuator saturation with industrial applications. IEEE Transactions on Systems, Man, and Cybernetics: Systems47(7): 1270–1283.
22.
WangCWenCGuoL (2020b) Adaptive consensus control for nonlinear multiagent systems with unknown control directions and time-varying actuator faults. IEEE Transactions on Automatic Control66(9): 4222–4229.
23.
WangLShiQLiuJ, et al. (2020a) Backstepping control of flexible joint manipulator based on hyperbolic tangent function with control input and rate constraints. Asian Journal of Control22(3): 1268–1279.
24.
WuZPengLXieL, et al. (2015) Stochastic bounded consensus tracking of second-order multi-agent systems with measurement noises based on sampled-data with general sampling delay. International Journal of Systems Science46(3): 546–561.
25.
YinYShiYLiuF, et al. (2019) Second-order consensus for heterogeneous multi-agent systems with input constraints. Neurocomputing351: 43–50.
26.
ZhangBSunXLiuS, et al. (2022) Distributed fault tolerant model predictive control for multi-unmanned aerial vehicle system. Asian Journal of Control24(3): 1273–1292.
27.
ZhangHLewisFQuZ (2011) Lyapunov, adaptive, and optimal design techniques for cooperative systems on directed communication graphs. IEEE Transactions on Industrial Electronics59(7): 3026–3041.
ZhaoBPengYSongY, et al. (2018) Sliding mode control for consensus tracking of second-order nonlinear multi-agent systems driven by Brownian motion. Science China Information Sciences61(7): 1–8.
30.
ZhaoLJiaY (2016) Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults. International Journal of Systems Science47(8): 1931–1942.
31.
ZouYMengZ (2019) Coordinated trajectory tracking of multiple vertical take-off and landing UAVs. Automatica99: 33–40.
