Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition

Research article (IEEE Transactions on Neural Networks and Learning Systems, 2022) · cited 34× · AI/ML
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Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition

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Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition. Retrieved May 24, 2026, from https://4ort.xyz/entity/composite-learning-adaptive-tracking-control-for-full-state-constrained-multiagent-systems-without-using-the-feasibility
MLA “Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/composite-learning-adaptive-tracking-control-for-full-state-constrained-multiagent-systems-without-using-the-feasibility.
BibTeX @misc{4ortxyz_composite-learning-adaptive-tracking-control-for-full-state-constrained-multiagent-systems-without-using-the-feasibility_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition}}, year = {2026}, url = {https://4ort.xyz/entity/composite-learning-adaptive-tracking-control-for-full-state-constrained-multiagent-systems-without-using-the-feasibility}, note = {Accessed: 2026-05-24}}
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