diff --git a/feed.xml b/feed.xml index f7311f1..cdde3e5 100644 --- a/feed.xml +++ b/feed.xml @@ -1,2 +1,2 @@ -Jekyll2024-06-17T14:27:14+00:00https://eklavya.sravjti.in/feed.xmlblankA simple, whitespace theme for academics. Based on [*folio](https://github.com/bogoli/-folio) design. +Jekyll2024-06-21T14:08:16+00:00https://eklavya.sravjti.in/feed.xmlblankA simple, whitespace theme for academics. Based on [*folio](https://github.com/bogoli/-folio) design. \ No newline at end of file diff --git a/projects/LQR_Balancer/index.html b/projects/LQR_Balancer/index.html new file mode 100644 index 0000000..eadf5fe --- /dev/null +++ b/projects/LQR_Balancer/index.html @@ -0,0 +1,292 @@ + + + + + + + + + + + + + LQR Balancer | Eklavya 2024 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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LQR Balancer

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Self-balancing Wall-E using LQR

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Project DomainsMentorsProject Difficulty
Control Systems, Embedded SystemsNilay Seth, ShankariMedium to Hard
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Project Description

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Imagine the challenge of balancing Wall-E without relying on the conventional PID controller, but instead employing an advanced controller like LQR. +New to LQR? Let’s delve into what it entails. Linear Quadratic Regulators (LQR) stand out as optimal controllers renowned for their ability to effectively manage multiple control objectives within linear dynamic systems. Essentially, if we can describe our robot using a set of linear equations, LQR emerges as the go-to method for guiding the system towards a desired state with optimal efficiency.

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Delve deeper into the fascinating realm of Control Systems by exploring various other optimal controllers. By embarking on this journey, you can gain a comprehensive understanding of how these controllers operate and apply them to craft a custom control system for Wall-E, starting from scratch. +Take the opportunity to dive into the intricacies of coding and empowering Wall-E to perform tasks with precision and grace.

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Resources

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Outcome of the Project
+Closed loop Control

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GyroGlider

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