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of 9
pro vyhledávání: '"Mahmud, S M Nahid"'
Output Feedback Adaptive Optimal Control of Affine Nonlinear systems with a Linear Measurement Model
Real-world control applications in complex and uncertain environments require adaptability to handle model uncertainties and robustness against disturbances. This paper presents an online, output-feedback, critic-only, model-based reinforcement learn
Externí odkaz:
http://arxiv.org/abs/2210.06637
The objective of this research is to enable safety-critical systems to simultaneously learn and execute optimal control policies in a safe manner to achieve complex autonomy. Learning optimal policies via trial and error, i.e., traditional reinforcem
Externí odkaz:
http://arxiv.org/abs/2204.01409
The ability to learn and execute optimal control policies safely is critical to realization of complex autonomy, especially where task restarts are not available and/or the systems are safety-critical. Safety requirements are often expressed in terms
Externí odkaz:
http://arxiv.org/abs/2110.00271
This paper addresses the problem of online inverse reinforcement learning for systems with limited data and uncertain dynamics. In the developed approach, the state and control trajectories are recorded online by observing an agent perform a task, an
Externí odkaz:
http://arxiv.org/abs/2008.08972
Reinforcement learning has been established over the past decade as an effective tool to find optimal control policies for dynamical systems, with recent focus on approaches that guarantee safety during the learning and/or execution phases. In genera
Externí odkaz:
http://arxiv.org/abs/2007.12666
In this paper, a concurrent learning based adaptive observer is developed for a class of second-order nonlinear time-invariant systems with uncertain dynamics. The developed technique results in uniformly ultimately bounded state and parameter estima
Externí odkaz:
http://arxiv.org/abs/1703.07068
Akademický článek
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Akademický článek
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Autor:
Mahmud SMN; School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United States., Nivison SA; Munitions Directorate, Air Force Research Laboratory, Eglin AFB, FL, United States., Bell ZI; Munitions Directorate, Air Force Research Laboratory, Eglin AFB, FL, United States., Kamalapurkar R; School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United States.
Publikováno v:
Frontiers in robotics and AI [Front Robot AI] 2021 Dec 16; Vol. 8, pp. 733104. Date of Electronic Publication: 2021 Dec 16 (Print Publication: 2021).
