Issue #5: July 22, 2024
Our co-founder Paul Dennig Sr. invites you
to uncover flight autonomy and the fascinating science behind it!
What’s Inside This Issue?
- Concepts and Terminology: Discover concepts and terminology introduced in the featured article.
- Featured Article: Join Paul Sr. as he guides you through the fascinating world of autonomous flight.
- About the Author: Read about how Paul Sr. got interested in flight autonomy.
- Hands-On Activities: Engage in a fun activity that provides the basics in flight autonomy.
- Equity and Sustainability through Flight Autonomy: Explore how flight autonomy can advance equity and sustainability.
- Glossary: Recap key concepts and terminology from the featured article.
Concepts and Terminology
Control theory helps us create an autopilot for a machine. These autopilots figure out how to adjust themselves while they are in operation. This approach keeps the machines working the way you want, even if conditions change rapidly.
A control system is a setup that generally uses sensors and feedback to automatically manage and adjust the operation of machines and devices to keep them working correctly.
Flight autonomy refers to the ability of aircraft, like drones or air taxis, to fly and navigate without direct human control, using sensors and computers to make decisions.
A barometer is a device used to measure atmospheric pressure, which helps in predicting weather changes and for calculating altitude.
LiDAR, or Light Detection and Ranging, is a remote sensing method that uses pulsed laser beams to measure distances. By recording the time it takes for the light to bounce back from objects, LiDAR calculates distance and can also create a highly accurate 3D map of the surrounding environment.
Featured Article
Unveiling the Secrets of Control Systems and Autonomy
By Paul Dennig Sr., PhD
Introduction
Ever wonder how your house stays comfy or a plane stays on course? It’s control theory, a powerful engineering concept that you might not have heard of but can easily understand.
Control theory helps designers create everything from cars to factories, even making self-driving vehicles possible. The goal of control theory is to create a control system.
A control system is like a manager overseeing operations, whether it’s factory equipment (a plant) or the steps in a production process. Our bodies also rely on intricate control systems: blinking to keep our eyes lubricated and regulating heartbeats automatically to ensure smooth blood flow.
Within a control system, tasks are managed with precision to achieve specific goals within a larger setup. For example, consider a faucet: it controls water flow by adjusting a handle, ensuring you receive just the right amount for washing your hands or filling a glass, responding dynamically to your needs. Similarly, a thermostat regulates temperature by monitoring the room and adjusting heating or cooling to maintain comfort levels, responding to changes in the surrounding environment.
There are two main control methods:
- Open Loop: Set it and forget it, like using a toaster. Once you set the timer and press the lever, the toaster heats for the set time without adjusting based on how toasted the bread gets. It works, but watch out for burnt toast!
- Closed Loop: Uses sensors for feedback, like a thermostat automatically adjusting an air conditioner to maintain a desired set temperature. Alternatively, imagine a toaster that watches your bread and stops before burning the toast!
Modern control systems are even smarter. Smart thermostats learn your habits and adjust settings automatically!
Control theory is everywhere, making our lives easier. Understanding it opens doors to exciting possibilities in engineering and beyond!
What’s Autonomy?
Control systems are great at running things like equipment, but sometimes like us, they need additional information, for example, when situations become unpredictable. By adding access to artificial intelligence, or AI, for example, systems have a better chance to run without humans. When we add more to a basic control system, such as AI, we say that these more sophisticated systems practice “autonomy,” or become “autonomous control systems.” When these autonomous systems make decisions based on their programming, they are utilizing math and science to manage themselves.
Autonomous Flying Vehicles
Ever seen all the hype about self-driving cars? Well, buckle up for self-flying vehicles! They might seem like science fiction, but they’re actually closer than you think.
Let’s take a closer look at how a regular hobby drone works first. Picture a nimble quadcopter with four robust propellers whizzing through the air, powered by rechargeable batteries that keep it soaring for extended flights. But how does it fly exactly where you want it to? That’s where the brains come in – a tiny computer similar to the one in your phone! Special sensors act like eyes and ears for the drone, telling it how it’s positioned and moving. These sensors are super tiny and affordable! One example is a tiny chip called an MPU6050 that can sense rotation, gravity, and acceleration – all for under $5!
Now, imagine scaling up this technology for a larger vehicle capable of transporting people and cargo! Imagine robust electric motors fueled by larger, eco-friendly batteries. Add super-smart AI to plan the best routes and avoid traffic jams… in the sky! Companies around the world, like Joby Aviation, are already developing these “air taxis” – check out their hex-a-copter design!
Joby Aviation’s five-seat air taxi
How does it stay on course? Just like the little hobby drone, the air taxi uses its sensors to pinpoint its location and see how far it is from its destination. Global Positioning System (GPS) sensors tell it exactly where it is, while barometer chips measure changes in atmospheric pressure to determine its altitude! The computer then figures out how to adjust the flight path to get back on track – that’s what control theory is all about! This system constantly monitors and corrects for errors, keeping the taxi flying smoothly.
You now have a good understanding of how an air-taxi navigates. It relies on a complex network of sensors, including LiDAR for 3D mapping, radar for obstacle detection (and also altitude), and cameras for visual data, to pinpoint its location, avoid obstacles, and continuously calculate any discrepancies between its current position and its intended destination. This difference is called the “deviation” and is a natural part of the navigation process. Through ongoing adjustments based on these sensor data, the air-taxi refines its position, ensuring it stays on course for a smooth journey. This core principle of minimizing “deviation” or “error” is fundamental to control theory.
Image Credit: Single-person air taxis developed by FlyNow Aviation
This is just the beginning! Imagine this technology applied to everyday life — from self-driving cars navigating traffic to smart homes adjusting to your needs. Control theory could revolutionize healthcare with prosthetic limbs mimicking natural animal movement, enhancing mobility for amputees. In robotics, agile machines could navigate terrain like animals, improving efficiency in tasks from rescue missions to farming to building homes to exploration. The possibilities are endless!
To Learn More:
For a deeper dive into the concepts we’ve covered and to broaden your understanding, explore these engaging web video playlists:
- Explore a curated series of videos that break down automatic control basics: Automatic Control Basics Playlist , and
- For a fascinating journey into the field of control theory, visit: Fascinating Field of Automatic Control
To master control theory, you’ll need a strong grasp of basic arithmetic, geometry, and calculus—essential foundations for understanding its principles. As you advance from high school, each step prepares you to explore exciting disciplines in college.
Control theory is highly versatile, and is applied to fields like aerospace, biomedical sciences, chemical processes, electrical systems, energy production, industrial automation, mechanical operations, and more. Proficiency in Computer Science is increasingly essential, as modern control systems integrate computer principles and programming for efficient operations and to add features like AI to make them autonomous. We’ve introduced basic control theory and autonomous systems here, but as you can imagine, there is much more that can be done, and there is no end to the exciting challenges they pose.
An important consideration in all areas of life where AI is used is, “is it safe to use? Can we trust it?” This is especially true where transportation is concerned, such as with autonomous air taxis. Would you enjoy one day helping to figure out the balance of rewards and risks of adding AI to control systems?
Embrace the challenge and start your journey today!
About the Author
Paul Dennig, Sr. began his journey of understanding electronics as a boy, soldering and screwing together electronic kits at home. Inspired by the space program, Paul Sr. also built models, including rockets and radio-controlled airplanes. He later taught these skills to Paul Jr. While in college, the basic principles of control systems, RADAR, and computers were introduced in Paul Sr.’s electrical engineering classes. He got even more practice in graduate school while adding knowledge of materials processing and related equipment. Over many years of working in the electronics industry, he focused on topics such as digital design, sensors, rechargeable batteries, autonomous vehicles, power electronics, and more. Today, he hopes to encourage young people to explore the rewarding areas of STEM.
Hands-on Activities
Have you ever wondered how self-balancing scooters work? It’s all about control theory, and today you get to be the engineer!
Check out a FREE Ball & Beam Simulator here. Your mission: become a master of balance by controlling a virtual ball on a beam. On the left, you see a red ball that can roll on a white beam. The beam’s tilt is managed by a control system.
Image Credit: Daniele Benedettelli’s Ball and Beam System Simulator
The controller display uses “Gain” to show its control strength. In basic control techniques, you’ll find three types of gain:
- “P” for proportional, responding directly to distance from the target.
- “I” for integral, accumulating responses over time.
- “D” for differential, reacting to the rate of change in distance.
Here’s the challenge: the ball is a bit wobbly! Use the controller to keep it balanced. But there’s a twist: the controller has different settings that affect how it responds. Can you figure out the best settings to keep the ball balanced, even after you give it a nudge?
You can try these steps when getting started:
- Click on “Start Controller” and let the ball stabilize over the fulcrum (center spot).
- Move the blue pointer. You’ll see a small dot on the beam, also marking this new target position. When everything settles down, the error windows should turn green again.
- Click on “Hit the Ball” to see what happens.
- When the ball is stable again, try increasing the “D Gain” number from 20 to 50 in the “PID – Position” box. What can you now say if too much D gain, meaning too much ‘rate of change’ feedback, is used by the controller? Click “Stop Controller” to save yourself from getting a headache!
- Try more changes and combinations of them, knowing that you can revert back to the beginning conditions by clicking on the X to terminate the simulator session, then restart it.
Have fun!
Equity and Sustainability through Flight Autonomy
Flight autonomy plays a crucial role in advancing environmental equity and sustainability by enabling efficient, eco-friendly solutions to complex challenges. Here are five examples where flight autonomy can make a significant impact:
Rapid Medical Supply Delivery: Autonomous drones can swiftly deliver medical supplies to remote or disaster-stricken areas, reducing reliance on conventional transport and minimizing carbon emissions.
Image Credit: Government Technology
Precision Agriculture: Drones equipped with advanced sensors can optimize crop yields by precisely monitoring soil conditions and crop health, leading to reduced pesticide use and water consumption while maximizing productivity.
Image Credit: IoTech
Environmental Monitoring and Rescue Operations: Autonomous robots and drones are invaluable in monitoring environmental changes, assessing natural disasters, and assisting in rescue missions, thereby enhancing response times and minimizing human risk.
Image Credit: Skydio
Ocean and Marine Life Monitoring: Drones can survey marine ecosystems, monitor pollution levels, track marine life migrations, and assess coral reef health, contributing to ocean conservation and sustainable fisheries management.
Image Credit: blueye
Wildlife Conservation: Drones can monitor wildlife populations, track animal movements, and detect poaching activities without disturbing natural habitats, aiding conservation efforts.
Image Credit: ZenaDrone
Glossary
| Definition |
|---|
A barometer is a device used to measure atmospheric pressure, which helps in predicting weather changes. The pressure can be used to calculate altitude, too |
Control theory helps us create an autopilot for a machine. These autopilots figure out how to adjust themselves while they are in operation. This approach keeps the machines working the way you want, even if conditions change rapidly |
A control system is an autopilot setup that generally uses sensors and feedback to automatically manage and adjust the operation of machines and devices to keep them working correctly. Modern versions rely on digital computer chips. |
In control systems, deviation or error is how much the actual control value, such as position, differs from the desired value, showing how close or far the system is from its target or desired operation. |
Flight autonomy refers to the ability of aircraft, like drones or air taxis, to fly and navigate without direct human control, using sensors and computers to make decisions. |
In control systems, gain means how much a small change in one part of the system affects another part. It helps adjust signals to make things work smoothly. An example would be the volume setting when you listen to music. |
GPS, or Global Positioning System, is a technology that uses satellites to pinpoint locations on Earth accurately. It helps devices like phones and navigation systems find where they are and navigate to specific places. |
LiDAR, or Light Detection and Ranging, is a remote sensing method that uses pulsed laser beams to measure distances. By recording the time it takes for the light to fly out to objects and bounce back from them, LiDAR can calculate the distance to the object. It can even create a highly accurate 3D map of the surrounding environment. |
Radar is a technology that uses radio waves to detect objects and determine their range, speed, and direction. It’s commonly used in aviation, weather forecasting, and military applications. |
Smart homes are houses with devices that can be controlled remotely or automatically, using a smartphone or voice commands, managing tasks like adjusting heating, lighting, security, and appliances for convenience and efficiency. |
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