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Questions tagged [control-theory]

Control theory in control systems engineering deals with the control of continuously operating dynamical systems.

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Reinforcement learning with two goal states [closed]

I implemented my first TD off-policy method for discrete states and discrete actions (increase or decrease to last executed action) on a patient in real time. Now I am extending my problem from one ...
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Generalized Advantage Estimation

I have three questions regarding the paper High-Dimensional Continuous Control Using Generalized Advantage Estimation: 1) The authors define $\gamma$-just estimators below. My question is: Does the ...
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How to model this complex system?

I need some tips to approach a complex challenge. I have a system that consists of four connected units. Every unit has its own light bulb and temperature. First, the brightness of the bulb and ...
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How solve Markov decision process problems with continuous state space?

My problem considers a discrete-time linear time-invariant plant. The state space is continuous. The system needs to make decision at every time step. It is a MDP problem with more uncertainties in ...
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Why assume controls are independent of state estimation in Kalman Filter?

Here's the classic graphical model depiction of a Kalman Filter (or any form of Bayes filter for that matter). Why do we assume that the controls are independent of the previous state estimation? For ...
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Deriving the particle filter with driving-force/inputs/control-signal

Whenever the particle filter is derived (I used a different condition for $u_t$ as a solution to the nonlinear filtering problem; $x_{t+1} \mid x_t \sim f_{\theta}(x_{t+1} \mid x_t,u_t) \\ y_{t} \...
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Existence of ε-optimal Borel measurable policies in stochastic control

I am reading the book "Stochastic Optimal Control: The Discrete Time Case", by Bertsekas and Shreve (hereafter called "the Book"), and I recently observed that a statement made in page 10 of the book (...
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Template learning in Neural Network for control applicatication

Are there any advantages to using a neural network to mimic the output of a control system (also known as template learning). Are there any functioning examples of this technique in real world ...
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Using dynamic programming with n-step ahead predictors

Say I want to find the optimal control strategy involving a (partially) predictable stochastic process. My predictor is autocorrelated with white noise innovations: $$ p_t = \alpha p_{t-1} + \...
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Kalman filter equation derivation

I'm studying the Kalman Filter for tracking and smoothing. Even if I have understood the Bayesian filter concept, and I can efficiently use some of Kalman Filter implementation I'm stucked on ...