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Time-varying state constrained estimators-based command filtered quantized consensus control for nonlinear multiagent systems
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DOI：10.1002/rnc.6947.png)
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摘要
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This article investigates the command filtered backstepping quantized consensus control for the time-varying full-state constrained nonlinear multiagent systems based on unknown system dynamics estimators (USDE). First, different from the intelligent control and the USDE-based control methods, a novel time-varying state constrained (TVSC)-USDE is developed to estimate the unknown nonlinear dynamics and disturbances exactly with fewer parameters, where the states in TVSC-USDE satisfy the state constraints requirements. The proposed TVSC-USDE can reduce the computational burdens that caused by the online estimation of weights. Second, distinguish from current state constraints methods, by designing the integral barrier Lyapunov functions (IBLFs), the conservatism feasibility conditions are removed, which is more reasonable for the physical multiagent systems. Furthermore, the explosion of complexity (EOC) is a vital issue to tackle under the IBLFs backstepping control schemes. For this purpose, this article designs the command filters to gain the derivatives and handle the EOC problem. Further, to counterbalance the filtering errors, the error compensation signals are first developed in IBLFs-based control method. Finally, the input quantized signals are introduced for the limited bandwidth problem in multiagent network systems, and the proposed control approach can attain consensus tracking under low communication rates and small tracking errors.
Keyword:
command filtered control
explosion of complexity
IBLFs
input quantized
multiagent systems
期刊
IF:
3.2
论文数:
7.0K
被引数:
1.4W
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