Control from Approximate Dynamic Programming Using State-Space Discretization

\[\def\bigtimes{\mathop{\vcenter{\huge\times}}}\] Introduction In a recent post, principles of Dynamic Programming were used to derive a recursive control algorithm for Deterministic Linear Control systems. The challenges with the approach used in that blog post is that it is only readily useful for Linear Control Systems with linear cost functions. What if, instead, we had a Nonlinear…

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Intro to Dynamic Programming Based Discrete Optimal Control

Intro Oh control. Who doesn’t enjoy having control of things in life every so often? While many of us probably wish life could be more easily controlled, alas things often have too much chaos to be adequately predicted and in turn controlled. While lack of complete controllability is the case for many things in life,…

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Predicting the Future – An Intro to Models Described by Time Dependent Differential Equations

In a previous post, Predicting the Future – An Intro, I briefly explained how prediction is approached and applications of such predictions. In this blog post, I am going to walk you through what it takes to make predictions using models described by time dependent differential equations. Please make note that this post will be…

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Predicting the Future – An Intro

In our day to day lives, we live with uncertainty about what might happen. What will the weather be like today? Will there be traffic on my way to work? Will I finally get the recognition and promotion I have been working for? In life, there’s many things we don’t have enough data to predict….

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