[begin transmission 1/?]

What's that? What do I do for a living? Are you sure you want to tread those waters?
No, I'm not an English or philosophy teacher. Nor do I live in a Christian convent.
I'm an electrical engineer. Underwhelmingly that's my quite plain, current title that doesn't do my skillset and duties justice.
Electrical engineering is supremely interdisciplinary, encompassing a variety of fields. Certainly more than you'd think.

It is not limited to being bent over a workbench soldering circuitry together, even though that can be fun in its own right.
For me that was all in a past life, when I was a hungry (literally and figuratively) undergraduate student.
Burnt fingers and popped capacitors...the joys and horrors of analogue electronics. All in a rite of passage, I suppose.
No, these days the source of my headaches are computer simulations, particularly as they pertain to the defense industry.

You wouldn't know it by talking to me, as I tend to shy away from discussing technical matters with laypeople.
So instead I vociferously state my opinions on things nearly everyone has input on: politics and culture.
Also, dealing w/ impersonal, cold machines and sterile mathematics day-in and day-out makes me crave the humanities.
Okay, so I'll try to explain things as simply and cleanly as possible; but these things are complex: consider this fair warning.

If you're mathematically-inclined, get your coffee, get your pastry, settle in and enjoy the brief lecture.
If you're not...I promise, we'll take things slow. I'll start w/ the basics; it's good practice for me anyway.

Easy Mode: Systems Theory

Let us first begin w/ an explanation of systems theory (if you really want to sound highfalutin, cybernetics; the term has assumed a very specific meaning nowadays, but has classically referred to the field of automatic control systems). In engineering, we are concerned w/ the manipulation of material and forces for the betterment of humanity. Towards this end, we organize the environment into systems: sets of components in the environment that are interconnected and embody principles that characterize it as a whole. These systems can be electrical, mechanical, biological, social, financial, etc. in nature. Now, it isn't enough to organize the environment into these discretized modules label them as systems and call it a day; we also need to be able to control these systems to harness them towards our ends. Here we cross into the realm of control theory, my formal academic field of study (to those interested, you'll find control engineering curricula within the mechanical or electrical engineering departments of most universities). In control engineering, we discretize systems further into sub-components, the central component being known as the process. Conceptualize the process as a component that simply receives an input and causally spits out an output, as illustrated below:

In order to control this process, we need to introduce components to the system. We can throw in a controller, the component that generates a control signal (more on that in a bit--sit tight) and an actuator, the component that takes the generated control signal and affects the process in some manner. This assembly, of a controller, actuator, and process is known canonically as an open-loop control system:

Notice here that the input into the open-loop control system is labeled as 'desired output response'. This is critical, as recall that we wish to harness these systems towards our ends (that is, we have a desired response from our system). Also notice that the output of the open-loop control system is labeled as 'output'. This is different from 'desired output'. Thus, I hope that you can logically infer that we can have an output that is not what we want. This is important to keep in mind, as the difference between output response and desired output response (AKA error) is absolutely INTEGRAL in describing the next tier of sophistication: the closed-loop control system. A closed-loop control system is identical to an open-loop control system, with the characteristic difference being that the output response is detected by sensors and fedback to the controller. Below is the block diagram:

So now that we've described a system abstractly to an adequate level of sophistication, it's time to illustrate a real-world example. What's something that is nearly universally experienced and understood...ah, alright. Let's use the boring, textbook example of driving a car. In this scenario, the closed-loop control system is you (the driver) and the car. The car is the process, your foot on the acceleration pedal is the actuator, and your brain is the controller. As you push down on the acceleration, the car moves forward; you see with your eyes the car moving forward, and you feel the acceleration with the proprioreceptors in your body. Therefore your eyes and proprioreceptors are sensors that feedback signals to your brain. If you notice that the road is disappearing under you car at an alarming rate, and you're being plastered into the back of the driver's seat, it is probably an indication that you're going much too fast; your brain will compute this difference between what is actually happening and what you want to happen (error) and generate a signal (control signal) to your foot to ease up on the acceleration.

To cite an example of a more engineering flavor, you could easily see how systems and control theory applies to robotics. To bring, say, the end effector (hand) of a robotic arm to a fixed point in 3D space, you must apply a particular voltage to a servomotor (conceptualize these as the 'joints' of the arm) to cause it to rotate, moving the attached linkage (the 'bone' of the arm) through space. Information regarding the position of the linkage could be coded by the resistance exhibited by a potentiometer (an electrical component that assumes a particular resistance depending on it's angular position) located at the joint.

Effectively, your potentiometer is the sensor, the servomotor is the actuator, and a computer or microcontroller would be the controller that receives the potentiometer data (i.e. a resistance value) and calculates an appropriate control signal (i.e. a command voltage) to send to the servomotor based off of that data. In order for the end effector of the robotic arm to be brought to a particular point in space, a specific voltage has to be sent to the servomotor. The voltage sent can be too little, resulting in us failing to reach the intended point and feelings of disappointment; or too much, resulting in us overshooting the intended point, sometimes to comical result:

Now, the above scenarios consider closed-loop control systems. This can easily be adapted into an open-loop control system. Merely cut off the feedback loop by driving with a blindfold on. Exciting as this may sound, I would not recommend this for any non-YoRHa units operating in the field. Although an open-loop control system sounds more basic than a closed-loop control system, it is still a very important concept to understand, as there are several real-world challenges concerned with the control of these types of systems.

I think that's a good place to stop for now. Most of this was conceptual in nature, making for a light and easy read (at least I hope). In the next section we will get a bit more technical, as I'll have to introduce dynamics into the conversation. But no worries, we won't do anything too crazy.

[end transmission 1/?]