Results 31 to 40 of about 4,643,442 (289)

Discrete Variational Optimal Control

, 2012
This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of variational ...
A. Iserles, A. Weinstein, A.I. Bobenko, A.M. Bloch, A.M. Bloch, D. Iglesias, David Martín de Diego, E. Hairer, E. Martínez, F. Bullo, F. Jiménez, Fernando Jiménez, I. Hussein, J. Cortés, J.C. Marrero, J.E. Marsden, J.E. Marsden, J.E. Marsden, J.E. Marsden, J.E. Marsden, M. Kobilarov, M. Kobilarov, M. Kobilarov, Marin Kobilarov, N. Bou-Rabee, R. Abraham, S. Ferraro, S. Ober-Blöbaum, T. Lee   +28 more
core   +1 more source

Minimax Optimal Control [PDF]

SIAM Journal on Control and Optimization, 2005
Summary: This paper provides a framework for deriving necessary conditions, in the form of a maximum principle, for minimax optimal control problems. The distinguishing feature of these problems is that the data depends on a vector \(\alpha\) of unknown parameters, and ``optimality'' is defined on a worst case basis, as \(\alpha\) ranges over the ...
openaire   +3 more sources

Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development

IEEE Access
For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes.
Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen   +5 more
doaj   +1 more source

Global optimal control of perturbed systems [PDF]

, 2006
We propose a new numerical method for the computation of the optimal value function of perturbed control systems and associated globally stabilizing optimal feedback controllers.
Grüne, Lars, Junge, Oliver
core   +4 more sources

Deception in Optimal Control

, 2018
In this paper, we consider an adversarial scenario where one agent seeks to achieve an objective and its adversary seeks to learn the agent's intentions and prevent the agent from achieving its objective.
Ornik, Melkior, Topcu, Ufuk
core   +1 more source

Optimal control and inverse optimal control by distribution matching [PDF]

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016
Optimal control is a powerful approach to achieve optimal behavior. However, it typically requires a manual specification of a cost function which often contains several objectives, such as reaching goal positions at different time steps or energy efficiency.
Arenz, O., Abdulsamad, H., Neumann, G.
openaire   +3 more sources

Estimation of travel time reduction for ice-breaking ships when considering ice information data

Annals of Glaciology
In light of the recent increase in polar shipping and potential future increase with continued climate change reliable routing in ice-covered waters becomes increasingly important for environmental, economic and safety concerns.
Bernhard Schmitz, Christine Eis, H. Jakob Bünger, Christof Büskens   +3 more
doaj   +1 more source

Optimal and adaptive control of underwater vehicles [PDF]

Modeling, Identification and Control, 1994
This article contains a continuous-time optimal and adaptive control scheme for underwater vehicles moving in six degrees of freedom. The control scheme is an extension of the algorithm ofJohansson (1990) and a modification of the algorithm found in ...
Svein I. Sagatun, Rolf Johansson
doaj   +1 more source

Obstacle Avoidance Control of the AGV With Actuator Dead Zones Based on Fixed-Time Disturbance Observers and Command Filtering

IEEE Access
This study explores an obstacle avoidance control approach that takes into account both actuator dead zones and unpredictable disturbances in environments with moving obstacles.
Pengfei Zhang, Yuanpei Ding, Ye Chen
doaj   +1 more source

Polynomial mechanics and optimal control

, 2015
We describe a new algorithm for trajectory optimization of mechanical systems. Our method combines pseudo-spectral methods for function approximation with variational discretization schemes that exactly preserve conserved mechanical quantities such as ...
Srinivasan, Akshay, Venkadesan, Madhusudhan   +1 more
core   +1 more source