“How can we analyze grand scale engineering projects without spending too much money?”
Engineering projects can really range in scale. They can go as large as skyscrapers pushing over a hundred floors, or as small as microdevices that inhabit the mystical world of quantum mechanics. However, if we want to perform any tests at this scale, it would be prohibitively expensive. So how can we use our engineering mindset to get around this problem? Well, we know that equations for physical phenomena tend to be the same regardless of scale. So what if we were to build a model at a more manageable size, perform our tests, retrieve the data, and then use the scale ratio to convert it? Well, this method known as dimensional similitude is used every day by engineers to drastically reduce costs. Dimensional similitude is often employed in wind tunnel tests when full scale aircraft become prohibitively expensive.
“How can we use a digital signal to control power appliances?”
Using sinusoidal analog signals for control applications has drawbacks. Specifically, the constantly changing signal can cause the resistors on a circuit to heat up and induce damage. However, how can we use our engineering mindset to fix this problem? Well, what if we were to replace this analog system with a discrete one operating at a duty cycle? That way we can imitate the perpetually switching signal while avoiding the issues that come along with it. This type of signaling is known as pulse-width modulation and is one of the fundamental ideas of modern control theory
“How can we optimize a nonlinear phenomenon using math?”
Linear programming is great for optimizing first order models. However, most real world systems are actually nonlinear in nature and thus require something further than linear programming. So how can we devise a method new, more optimal method? Well, let’s think about it. First, let’s boil everything down into matrices. Then, let’s introduce their constraints. The equation should now be in the form f(x) = 0.5*x^T*B*x – x^T*b subject to A1*x = c and A2*x = d, where x is the set of all independent variables, B and b are any quadratic objective function on these variables, and A1/c and A2/d are the inequality and equality constraints. Once we have the system set up, we can enter it into a computational package and achieve our results. This method is known as quadratic programming and is frequently used to solve problems fields ranging from energy analysis to finance
“Do some control systems have a zone with no feedback?”
Ideal controls systems are available to take in all possible frequencies. Some controls systems have a zone where the input frequency will return nothing. This region is known as the deadband and can be used to prevent unwanted side-effects.
“How can we measure the difference between a control signal and a half phase shift?”
When working with electronic amplifiers, the phase of an input signal might be shifted, which might introduce instability. And if this phase shift is greater than 180 degrees, then the system will be unstable. To standardize all measurements, electronics researchers have introduced the concept of a phase margin, or how far off from a 180-degree phase shift this new phase is. The phase margin can be calculated with the simple equation P_margin = |180-phase|.
“What is the margin of stability for a gain Bode Plot?”
One of the most useful features of a Bode Plot is the ability to find the stability of a system. One way to do that is to find the frequency at which the phase shift becomes 180 degrees, get the amplitude of the gain at the point, and then make a gain margin extending out to both sides equal to the magnitude of 1/|Amplitude value|, such that anything within that range will be stable.
“What are steady oscillations called?”
Many physical systems exhibit oscillating behavior. However, the natures of these oscillations can be different from one another. And in the most ideal oscillations, the amplitude is constant and unchanging. These oscillations are known as undamped oscillations and are rarely found outside equations and simulations.