40 lines
1.8 KiB
Markdown
40 lines
1.8 KiB
Markdown
# Multi-Purpose MPC
|
|
|
|
1. [Introduction](#introduction)
|
|
2. [Implementation Details](#implementation-details)
|
|
1. [Map](#map)
|
|
1. [Model Predictive Controller (MPC)](#model-predictive-controller)
|
|
3. [How-To](#how-to)
|
|
4. [Limitations and Outlook](#limitations-and-outlook)
|
|
|
|
## Introduction
|
|
|
|
In this repository you find an implementation of a multi-purpose Model Predictive Controller. The controller was implemented as a contribution to the [Automatic Control Project Course (EL2425)](https://www.kth.se/student/kurser/kurs/EL2425) at KTH Royal Institute of Technology, Stockholm.
|
|
The developed algorithm was tested on a 1:10 RC car provided by [KTH Smart Mobility Lab](https://www.kth.se/dcs/research/control-of-transport/smart-mobility-lab/smart-mobility-lab-1.441539). The test scenarios comprised the following three tasks:
|
|
|
|
1. Reference Path Tracking
|
|
2. Time-Optimal Driving
|
|
3. Obstacle Avoidance
|
|
|
|
The controller is implemented in a way that enables its application to all three tasks by merely tuning the weight matrices of the underlying optimization problem. The illustration below shows the obstacle avoidance task in simulation.
|
|
|
|
The rest of this readme is structured as follows. In [Section 2](##Components) we will present an overview of the entire system and discuss all fundamental components of the implementation in detail. In [Section 3](##How-To) we will provide guidelines for using the implementation in simulation and practice. [Section 4](##Limitations) will be dedicated to analyzing limitations of the current version of the controller and outline potential extensions of the implementation.
|
|
|
|
## Implementation Details
|
|
|
|
<p align="center">
|
|
<img src="MPC_Framework.png">
|
|
</p>
|
|
|
|
### Map
|
|
|
|
### Reference Path
|
|
|
|
### Spatial Bicycle Model
|
|
|
|
### Model Predictive Controller
|
|
|
|
## How-To
|
|
|
|
## Limitations and Outlook
|