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eess.SY2023
Reach-avoid Analysis for Sampled-data Systems with Measurement Uncertainties
Taoran Wu, Dejin Ren, Shuyuan Zhang +2
Digital control has become increasingly prevalent in modern systems, making continuous-time plants controlled by discrete-time (digital) controllers ubiquitous and crucial across i…
cs.LG2023★ 1 cited
Repairing Deep Neural Networks Based on Behavior Imitation
Zhen Liang, Taoran Wu, Changyuan Zhao +4
The increasing use of deep neural networks (DNNs) in safety-critical systems has raised concerns about their potential for exhibiting ill-behaviors. While DNN verification and test…
eess.SY2023
Provable Reach-avoid Controllers Synthesis Based on Inner-approximating Controlled Reach-avoid Sets
Jianqiang Ding, Taoran Wu, Yuping Qian +2
In this paper, we propose an approach for synthesizing provable reach-avoid controllers, which drive a deterministic system operating in an unknown environment to safely reach a de…