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# Featured Tutorial

## Training a Reinforcement Learning Agent to Balance an Inverted Pendulum

In this tutorial, we cover how to train a controller for a complex system using Brax

## Robotic Arm Control with MuJoCo

In this tutorial we demonstrate how to control a robotic arm using the Collimator library and the MuJoCo physics engine

## State Estimation with Kalman Filters

In this tutorial, we show how convenient Collimator makes it to use a Kalman Filter to estimate the state of a pendulum to better inform an LQR controller

## Universal Differential Equations

In this tutorial we learn how to use neural networks to learn Universal Differential Equations

## Training a Multilayer Perceptron in Collimator

In this tutorial, we train a Multilayer Perceptron (MLP) using Collimator

## Finding Limit Cycles

In this tutorial, we teach a robot to walk on two legs using limit cycles

## Trajectory Optimization and Stabilization

We take a look at the Hermite-Simpson collocation method and finite-horizon LQR control for optimizing the trajectory of an acrobot.

## Linear Model-predictive Control

Model Predictive Control is a somewhat advanced technique for achieving a control output target trajectory. This tutorial takes you through the process of how to implement it using Collimator.

## Battery design parameter estimation - Part 3

In this chapter, we use the battery model that we developed previously, along with experimental data to better optimize our model.

## Battery design parameter estimation - Part 2

In this installment, we optimize the parameters of our battery model using synthetic data

## Battery design parameter estimation - Part 1

In this first part of a three-part series, we walk you through developing an equivalent circuit model (ECM) of a battery pack in Collimator

## F16 jet design

In this tutorial, we will show how to model nonlinear aircraft dynamics in Collimator. We will use the F16 model as a case study. The F16 dynamics were firstly introduced in NASA Technical Paper No. 1538, 1979. A reduced fidelty version is written in Fortran for the F16. Here, we will build the F16 nonlinear model in Collimator and investigate how to run an open loop simulation at different operating points...

## DC motor position controller design

Collimator is by far the best modeling and simulation software that I have used. Using the block diagrams that Collimator provides has allowed me to simplify my code and shift the time I was spending writing convoluted scripts back to my research!
R&D Researcher, Control Systems
Collimator is head and shoulders above the rest. I’ve found modeling to be very easy and straightforward. I’ve also saved a bunch of time and money while running my simulations. The same simulations that would take hours to run on my local PC run in minutes.
Control Systems Engineer, Consumer Electronics
Collimator proved to be the best solution for me because of how easy it was to get data from our back end, use that to create synthetic data, and then move that data into my neural net for training.
Automation Engineer, Technology Startup
It is amazing to use Python, run on a web browser and collaborate on the cloud […] This is undoubtedly 10x better than what I've used before!
GNC Engineer, Aerospace and Defense Manufacturing