There’s a line from the original Star Trek where Khan says, “Improve a mechanical device and you may double productivity, but improve man and you gain a thousandfold.” Joan Horvath and Rich Cameron have the same idea about improving education, particularly autodidacticism or self-learning. They share what they’ve learned about acquiring an intuitive understanding of difficult math at the Hackaday Superconference and you can watch the newly published video below.
The start of this was the pair’s collaboration on a book about 3D printing science projects. Joan has a traditional education from MIT and Rich is a self-taught guy. This gave them a unique perspective from both sides of the street. They started looking at calculus — a subject that scares a lot of people but is really integral (no pun intended) to a lot of serious science and engineering.
You probably know that Newton and Leibniz struck on the fundamentals of calculus about the same time. The original papers, however, were decidedly different. Newton’s approach was more physical and less mathematical. Leibniz used formal logic and algebra. Although both share credit, the Leibniz notation won out and is what we use today.
Continue reading “Understanding Math Rather Than Merely Learning It”
If you went to engineering school, you probably remember going to a lot of calculus classes. You may or may not remember a lot of calculus. If you didn’t go to engineering school, you will find that there’s an upper limit to how much electronics theory you can learn before you have to learn calculus. Now imagine Khan Academy, run by an auctioneer and done without computers. Well, you don’t have to imagine it. Thinkwell has two videos that purport to teach you calculus in twenty minutes (YouTube, embedded below).
We are going to be honest. If you need a refresher, these videos might be useful. If you have no idea how to do calculus, maybe these are going to whiz by a little fast. However, either way, the videos have some humor value both from the FedEx commercial-style delivery to the non-computerized graphics (not to mention the glass-breaking sound effects). Of course, the video is about ten years old, but that’s part of its charm.
Continue reading “Calculus in 20 Minutes”
Mathematics, as it is taught in schools, sometimes falls short in its mission to educate the pupils. This is the view of [Joan Horvath] and [Rich Cameron], particularly with respect to the teaching of calculus, which they feel has become a purely algebraic discipline that leaves many students in the cold when it comes to understanding the concepts behind it.
Their Hacker Calculus project aims to address this, by returning to [Isaac Newton]’s 1687 seminal work on the matter, Philosophiae Naturalis Principia Mathematica. They were struck by how much the Principia was a work of geometry rather than algebra, and they are seeking to return to [Newton]’s principles in a bid to make the subject more accessible to students left behind when it comes to derivatives and integrals. They intend to refine the geometric approach to create a series of practical items to explain the concepts, both through 3D printed items and through electronics.
We can see that this is an approach that has considerable merit, given that most Hackaday readers will have at some time or other sat through a maths lesson and come away wondering what on earth the teacher was talking about and having been baffled by further attempts to explain it through impenetrable maths-speak. If you were the kid who “got” calculus when the relationship between speed and acceleration – another thing we have [Newton] to thank for describing – was explained in your physics lessons, then you will probably understand.
The pair have some Hackaday Prize history, you may remember them from such previous entries as their 3D prints for the visually impaired project from last year.
The first time I was in school for electrical engineering (long story), I had a professor who had never worked in the industry. I was in her class and the topic of the day was measuring AC waveforms. We got to see some sine waves centered on zero volts and were taught that the peak voltage was the magnitude of the voltage above zero. The peak to peak was the voltage from–surprise–the top peak to the bottom peak, which was double the peak voltage. Then there was root-mean-square (RMS) voltage. For those nice sine waves, you took the peak voltage and divided by the square root of two, 1.414 or so.
You know that kid in the front of the class? They were in your class, too. Always raising their hand with some question. That kid raised his hand and asked the simple question: why do we care about RMS voltage? I was stunned when I heard the professor answer, “I think it is because it is so easy to divide by the square root of two.”
Continue reading “Root Mean Square”
It was Stardate 2267. A mysterious life form known as Redjac possessed the computer system of the USS Enterprise. Being well versed in both computer operations and mathematics, [Spock] instructed the computer to compute pi to the last digit. “…the value of pi is a transcendental figure without resolution” he would say. The task of computing pi presents to the computer an infinite process. The computer would have to work on the task forever, eventually forcing the Redjac out.
Calculus relies on infinite processes. And the Arduino is a (single thread) computer. So the idea of running a calculus function on an Arduino presents a seemingly impossible scenario. In this article, we’re going to explore the idea of using derivative like techniques with a microcontroller. Let us be reminded that the derivative provides an instantaneous rate of change. Getting an instantaneous rate of change when the function is known is easy. However, when you’re working with a microcontroller and varying analog data without a known function, it’s not so easy. Our goal will be to get an average rate of change of the data. And since a microcontroller is many orders of magnitude faster than the rate of change of the incoming data, we can calculate the average rate of change over very small time intervals. Our work will be based on the fact that the average rate of change and instantaneous rate of change are the same over short time intervals.
Continue reading “Running Calculus on an Arduino”
If I asked you to find the area of a square, you would have no problem doing so. It would be the same if I asked you to find the volume of a cone or rectangle or any other regular shape. You might have to turn to Google to get the proper formula, but it would be a trivial process nonetheless. But what if I asked you to find the volume of some random vase sitting on a kitchen counter? How does one go about finding the volume of irregular shapes?
One way would be to fill the vase with much smaller objects of a known volume. Then you could add up the smaller volumes to get an estimate of the total volume of the vase. For instance, imagine we fill the vase with marbles. A marble is a sphere, and we can calculate the volume of each marble with the formula 4/3πr3. We count all of our marbles and multiply the total by the volume of a single marble and arrive at our answer. It is not perfect, however. There is a lot of empty space that exists between the marbles as they fill the vase. We are forced to conclude that our estimated volume will be lower that the actual volume.
It would be about this time when our good friend Isaac Newton would ask the question “What if you made the marbles smaller?” Reducing the size of each marble would reduce the empty space that exists between them as they pile up in the vase, giving us a more accurate total volume. But how small? Is there a limit to how small we can make them? “Do not trouble yourself with the limit.” says [Newton]. “You will find that as you make the marbles smaller and smaller, you will begin to converge on a single number – and that number will be the exact volume of your vase.”
Reducing the size of the marble to get a more exact volume demonstrates the idea of the integral – one of the two fundamental principles of The Calculus. The other principle is known as the derivative, which we explained in our previous article by taking a very careful and tedious examination of an arrow in flight. In this article, we shall take the same approach toward the integral. By the end, you will have a fundamental understanding of what the integral is, and more importantly, how it works. Our vase example gives you a good mental image of what the integral is all about, but it is hardly a fundamental understanding of it. Just how do you make those marbles smaller? To answer this question, let us look again at one of Zeno’s moving arrows.
Continue reading “How to Find a Lost Drone with the Integral”
Control systems are all around us, and understanding them is going to make you much better at hardware design. In the last article — Beyond Control: The Basics of Control Systems — we looked at an overview of what a control systems are in general with the example: “everything in between water and time is a control system”. We also observed control systems in nature, where I described my keen ability to fill a glass of water without catastrophic results. That discussion involved the basic concept of a block diagram (without maths) and we expanded that a bit to see what our satellite dish example would look like (still without maths).
I promised some big ugly maths in this article, and we’ll get to that in a bit, never you fear. First let’s have a look at how some basic elements: resistors, inductors, and capacitors are defined in the time domain. Don’t let these first few definitions turn you off. No matter how you feel about calculus, you don’t necessarily need to fully understand each equation. What’s more important is how the equations themselves combine to solve the circuit. Also important is that I will do everything possible to get out of doing difficult math. So stick with me through the article and you’ll learn that agony-saving trick for yourself!
A quick recap on transfer functions before we get going might be beneficial. A control system is used to define electromechanical behavior. For example: our satellite dish (from the previous article) at some point will need to be moved from one position to another position and as control engineers it is our job to determine just how this action will take place. I’m not talking about setting the mood for the big emotional robotic rotation, more like: not damaging the equipment or any people that might be nearby when moving the dish. For many reasons the dish would need to be moved with extreme care and in a very precise manner. The control system is the mathematical definition of that movement. Often the maths of the definition are nasty differential equations, (remember I’m avoiding any math that can be avoided, right?) so, instead of using differential equations to define the system, the transfer function will define the system with algebra, relating the output of the system to the input.
Continue reading “Beyond Control: Maths of a Control System”