Results 281 to 290 of about 84,997 (313)
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2011
This chapter deals with the optimal control of a noisy linear system, the state of which is not entirely available, i.e., which requires a state reconstructor in the control loop. Since the system is submitted to random influences, a filter, e.g. an optimal filter such as the Kalman filter, will be used.
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This chapter deals with the optimal control of a noisy linear system, the state of which is not entirely available, i.e., which requires a state reconstructor in the control loop. Since the system is submitted to random influences, a filter, e.g. an optimal filter such as the Kalman filter, will be used.
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1971
So far we have applied the Kalman filter to systems which were subjected to random disturbances but were not controlled. Very briefly we turn now our attention to the case were we wish to employ measurements to control a system in some optimal manner. Only the simplest problem will be discussed here.
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So far we have applied the Kalman filter to systems which were subjected to random disturbances but were not controlled. Very briefly we turn now our attention to the case were we wish to employ measurements to control a system in some optimal manner. Only the simplest problem will be discussed here.
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Sufficient Conditions for the Optimality of a Stochastic Control
Journal of the Society for Industrial and Applied Mathematics Series A Control, 1965Sufficient conditions for optimal stochastic control of diffusion processes governed by vector equations satisfying local Lipschitz ...
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Optimal Controller Switching for Stochastic Systems
1999Presents a solution to certain problems in switched controller design for stochastic dynamical systems. The main result is a separation theorem for partial information systems. This result is then used to convert the partial information stochastic control problem to a complete information stochastic control problem.
Efstratios Skafidas +3 more
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1998
Abstract This chapter gives a self‐contained introduction to optimal control of stochastic differential equations. We derive the Hamilton‐Jacobi‐Bellman equation as well as a verification theorem. The general theory is then applied to optimal consumption and investment problems.
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Abstract This chapter gives a self‐contained introduction to optimal control of stochastic differential equations. We derive the Hamilton‐Jacobi‐Bellman equation as well as a verification theorem. The general theory is then applied to optimal consumption and investment problems.
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On the Existence of Optimal Stochastic Controls
Journal of the Society for Industrial and Applied Mathematics Series A Control, 1965openaire +2 more sources
Maximum principle for the stochastic optimal control problem with delay and application
Automatica, 2010Zhen Wu
exaly
A General Stochastic Maximum Principle for Optimal Control Problems
SIAM Journal on Control and Optimization, 1990Shige Peng
exaly