Results 241 to 250 of about 22,276,625 (298)
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2018
This chapter considers LQG optimal controls for input and state delayed systems. LQG controls use output feedback ones while LQ controls in the previous chapter require state feedback ones. State observers or filtered estimates are obtained from inputs and outputs to be used for LQG controls. First, finite horizon LQG controls are dealt with, which are
Wook Hyun Kwon, PooGyeon Park
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This chapter considers LQG optimal controls for input and state delayed systems. LQG controls use output feedback ones while LQ controls in the previous chapter require state feedback ones. State observers or filtered estimates are obtained from inputs and outputs to be used for LQG controls. First, finite horizon LQG controls are dealt with, which are
Wook Hyun Kwon, PooGyeon Park
openaire +1 more source
A mean-field optimal control formulation of deep learning
Research in the Mathematical Sciences, 2018Recent work linking deep neural networks and dynamical systems opened up new avenues to analyze deep learning. In particular, it is observed that new insights can be obtained by recasting deep learning as an optimal control problem on difference or ...
W. E, Jiequn Han, Qianxiao Li
semanticscholar +1 more source
2007
The most important job of industrial robots is moving between two points rest-to-rest. Minimum time control is what we need to increase industrial robots productivity. The objective of time-optimal control is to transfer the end-effector of a robot from an initial position to a desired destination in minimum time.
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The most important job of industrial robots is moving between two points rest-to-rest. Minimum time control is what we need to increase industrial robots productivity. The objective of time-optimal control is to transfer the end-effector of a robot from an initial position to a desired destination in minimum time.
openaire +1 more source
Optimal Control of Partial Differential Equations
Applied Mathematical Sciences, 2021A. Manzoni, A. Quarteroni, S. Salsa
semanticscholar +1 more source
The intelligent critic framework for advanced optimal control
Artificial Intelligence Review, 2022Ding Wang, Mingming Ha, Mingming Zhao
semanticscholar +1 more source
1987
In the long history of mathematics, stochastic optimal control is a rather recent development. Using Bellman’s Principle of Optimality along with measure-theoretic and functional-analytic methods, several mathematicians such as H. Kushner, W. Fleming, R. Rishel. W.M. Wonham and J.M.
openaire +1 more source
In the long history of mathematics, stochastic optimal control is a rather recent development. Using Bellman’s Principle of Optimality along with measure-theoretic and functional-analytic methods, several mathematicians such as H. Kushner, W. Fleming, R. Rishel. W.M. Wonham and J.M.
openaire +1 more source
CasADi: a software framework for nonlinear optimization and optimal control
Mathematical Programming Computation, 2018Joel A. E. Andersson +4 more
semanticscholar +1 more source
Design of Optimal Feedback for Structural Control, 2021
I. Halperin, G. Agranovich, Y. Ribakov
semanticscholar +2 more sources
I. Halperin, G. Agranovich, Y. Ribakov
semanticscholar +2 more sources