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pro vyhledávání: '"Zeng, Shen"'
Model predictive control (MPC) has proven useful in enabling safe and optimal motion planning for autonomous vehicles. In this paper, we investigate how to achieve MPC-based motion planning when a neural state-space model represents the vehicle dynam
Externí odkaz:
http://arxiv.org/abs/2310.08045
Publikováno v:
2022 American Control Conference (ACC), 2022, pp. 2084-2090
Control of machine learning models has emerged as an important paradigm for a broad range of robotics applications. In this paper, we present a sampling-based nonlinear model predictive control (NMPC) approach for control of neural network dynamics.
Externí odkaz:
http://arxiv.org/abs/2205.04506
Nonlinear model predictive control (NMPC) has gained widespread use in many applications. Its formulation traditionally involves repetitively solving a nonlinear constrained optimization problem online. In this paper, we investigate NMPC through the
Externí odkaz:
http://arxiv.org/abs/2205.04497
Publikováno v:
In Systems & Control Letters November 2024 193
We present and study a scheme for lossless causal compression of periodic real-valued signals. In particular, our technique compresses a vector-valued signal to a scalar-valued signal by mixing it with another periodic signal. The conditions for bein
Externí odkaz:
http://arxiv.org/abs/1812.02800
Publikováno v:
In IFAC PapersOnLine 2023 56(2):10089-10094
Autor:
Pan, You-lu, Zeng, Shen-xin, Hao, Rong-rong, Liang, Mei-hao, Shen, Zheng-rong, Huang, Wen-hai
Publikováno v:
In European Journal of Medicinal Chemistry 5 August 2022 238
Autor:
Zeng, Shen
In this paper, a first sample-based formulation of the recently considered population observers, or ensemble observers, which estimate the state distribution of dynamic populations from measurements of the output distribution is established. The resu
Externí odkaz:
http://arxiv.org/abs/1711.11095
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