Fuzzy Adaptive Quantized Control for a Class of Stochastic Nonlinear Uncertain Systems
By Zhi Liu, F. Wang, Yun Zhang, Chun Lung Philip Chen. IEEE Transactions on Cybernetics, 2016
298 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/ccd509f50580746bcda6d45f9ab304dbf8450605
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In Computational Theory and Mathematics
In Control and Systems Engineering
Citations in the corpus
- Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics (2017, background): “Many interesting control algorithms have been obtained in [11]–[15] for state-feedback control, while in [16]–[18] for output-feedback control.”
- Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems (2018, methodology): “Remark 2: Although there is an adaptive control scheme for system (8) in [16], the presented method in [16] is developed in the sense of infinite-time stability, they cannot guarantee the tracking performance in finite time in theory.”
- Prescribed Performance Cooperative Control for Multiagent Systems With Input Quantization (2020, background): “…ϕ im and ϕ in are the unknown bounded constants, f im ( ¯ x im ) and f in ( x in ) are the unknown smooth nonlinear functions, y i denotes the i th follower’s output, and u i is the control signal and the quantized input Q i ( u i ) is defined as the following form [43], [44]: with ¯ u ih = u ih ( 1”