ADEPT Framework Training CourseBalancing Robot DemonstratorCourse SummaryThe Balancing Robot Demonstrator Training Course provides a solid introduction to key features and concepts of the ADEPT Framework by taking a user through basic development, control and analysis of an rtx server using a Linux Bea-gleBone Blue (BBBlue) Single Board Computer (SBC) in a Balancing Robot (mobile inverted pendulum) configuration. This course starts basic and quickly builds skills to integrate and analyze a PID control loop model to balance the robot.

Primary Learning Points- Creating an ADEPT Framework- Using logical devices for IO- Connecting models and IO via data dictionaries (DCTs)- Python scripting for automation and control- Creating and integrating ADEPT Panel user interfaces- Implementing real-time schedules and triggers- Integrating C-code controls and models- Real-time data acquisition and analysis

Target AudienceThis is a beginner to intermediate level training course that is intended for both new and experienced users of the ADEPT Framework. No prior experience is required.

PrerequisitesThere are no prerequisites for this course.

Lesson 1: Introduction to ADEPT/rtx with a Linux BBBlueLearning Objectives

Topic Intro

Topic Hands-on

Topic Deep Dive

Open-source Debian RT Preempt Linux X

Data and control frameworks X

ADEPT Framework clients and rtx servers X

rtx server processes and threads X

Basic framework configuration X

ADEPT-VI and ADEPT-GD setup scripts and files X

ADEPT-VI data browser and data logging streams X

Python scripting for IO control and automation X

ADEPT Panel user interface control of Python scripts X

Lesson 2: Exploring the rtx Daemon on a Low-Cost SBCLearning Objectives

Topic Intro

Topic Hands-on

Topic Deep Dive

Creating an external data dictionary file X

Triggers and schedules for time-deterministic control X

Schedule groups with expression schedules for time-deterministic computation

X

Triggered Toggle schedules to duplicate IO control from Python scripts in Lesson 1

X

ADEPT Panel user interface control of triggers X

Building an ADEPT Panel with sliders widgets X

Timing performance of client vs server control X

Lesson 3: C-code Control, Data Handling and AnalysisLearning Objectives

Topic Intro

Topic Hands-on

Topic Deep Dive

Multi-core processor frameworks X

Multi-server distributed frameworks X

Adding a second model assembly X

Open loop C models for time-deterministic IO control X

C model functions to duplicate IO control from Les-sons 1 & 2

X

ADEPT Panel user interface control of C model X

Exploring Data Acquisition Service (DAS) X

ADEPT-GD plotting and Python scripting X

Lesson 4: Integrating Control Models with ADEPTLearning Objectives

Topic Intro

Topic Hands-on

Topic Deep Dive

Closed loop C model control in an ADEPT Framework X

Generating a data dictionary from a C model X

Explore built-in-test using an ADEPT Panel X

Building ADEPT Panels with user interface widgets X

Adjusting model step time and observing the impact on control performance

X

Lesson 5: Performance Analysis ADEPT, Python & NumPyLearning Objectives

Topic Intro

Topic Hands-on

Topic Deep Dive

ADEPT-GD plotting and visualization X

ADEPT-GD chart view components and customization X

ADEPT-GD interactive chart analysis tools X

Printing and saving charts in ADEPT-GD X

Automating data analysis using Python scripts X

Leveraging NumPy for data analysis X

Using data analysis to improve ADEPT Panel user interfaces

X