参数化复杂度
控制理论(社会学)
跟踪(教育)
输出反馈
自适应控制
计算机科学
控制(管理)
人工智能
算法
心理学
教育学
作者
Xianglei Jia,Shengyuan Xu
标识
DOI:10.1109/tac.2024.3394311
摘要
A new dynamic-scaling based global adaptive quantized control approach is proposed for nonlinear systems with input and state quantization, which reduces some conservatism of relevant results, including matched nonlinearities, global Lipschitz continuity and quantization error satisfying constant bound. A unique idea is used to deal with the quantized-state feedback problem; that is, the coefficient deviation problem in the decomposition of sector bounded quantizer is converted to that of solving novel coupled matrix inequalities. Also, a non-identification adaptive gain is introduced to compensate the mismatched nonlinearities and uncertainties. For a class of bounded differentiable reference signals, tracking error can be regulated to any small neighborhood of the origin as long as quantization dead-zone size is set small enough.
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