Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Patryk Deptula"'
Publikováno v:
IEEE Transactions on Automatic Control. 68:3618-3624
Publikováno v:
IEEE Transactions on Robotics. 39:605-624
Publikováno v:
IEEE Transactions on Automatic Control. 67:1356-1370
Distributed event- and self-triggered controllers are developed for approximate leader-follower consensus with robustness to adversarial Byzantine agents for a class of homogeneous multi-agent systems(MASs). A strategy is developed for each agent to
Publikováno v:
IEEE Transactions on Control Systems Technology. 30:740-754
For individuals with neuromuscular disorders (NDs) affecting the coordination and control of their legs, motorized functional electrical stimulation (FES) cycling serves as a rehabilitation strategy and offers numerous health benefits. A motorized FE
Publikováno v:
IEEE Transactions on Automatic Control. 66:4252-4258
Data-based, exponentially converging observers are developed for a monocular camera to estimate the Euclidean distance (and hence accurately scaled coordinates) to features on a stationary object and to estimate the Euclidean trajectory taken by the
Publikováno v:
IEEE Control Systems Letters. 4:743-748
This letter provides an approximate online adaptive solution to the infinite-horizon optimal control problem for control-affine continuous-time nonlinear systems while formalizing system safety using barrier certificates. The use of a barrier functio
Publikováno v:
IEEE Transactions on Robotics. 36:414-430
In this article, an infinite-horizon optimal regulation problem is considered for a control-affine nonlinear autonomous agent subject to input constraints in the presence of dynamic avoidance regions. A local model-based approximate dynamic programmi
Publikováno v:
AIAA SCITECH 2022 Forum.
Publikováno v:
IEEE Transactions on Robotics. 35:725-733
Autonomous agents are often tasked with operating in an area where feedback is unavailable. Inspired by such applications, this paper develops a novel switched system-based control method for uncertain nonlinear systems with temporary loss-of-state f
Publikováno v:
Handbook of Reinforcement Learning and Control ISBN: 9783030609894
This chapter discusses mixed density reinforcement learning (RL)-based approximate optimal control methods applied to deterministic systems. Such methods typically require a persistence of excitation (PE) condition for convergence. In this chapter, d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60f8956a90b401ba45977894248929a5
https://doi.org/10.1007/978-3-030-60990-0_5
https://doi.org/10.1007/978-3-030-60990-0_5