EEVacademy #6 - PID Controllers Explained

David explains PID controllers.
First part of a mini-series on control theory.
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[@MarcoTedaldi]

"control theory, feedback appreciated" 😊😊😂

[@mukil_saravanan]

Negative feedback is good 😆

[@MartynDavies]

00:17 "any feedback would be appreciated". Aha feedback: control theory. I see what you're doing there ;-)

[@uzimonkey]

I use PID controllers in a different context: game development. You'll often have a variable you need to drive to a value, but need to do it in a kind of smooth or organic way. Instead of writing a new way to do it every single time I need to do this, I use a PID controller. This is especially useful when other things are trying to effect this value as well, as the PID controller can react and push harder toward the set point and generally won't overshoot the set point. It is of course also very useful in physics simulations. I've made a hovercar just by making 4 "thrusters" on the bottom of the car, using the distance to the ground at that location as my setpoint and adding forces at those locations. If I were to try to program something like that, first I think it would take a while, but second I think I would end up with something a lot like a PID controller. They're just useful all over the place in gamedev. I also like to think in simplified terms, usually I'm not doing equations and figuring things out exactly in gamedev, it's more of a "put values in until it looks right" kind of task. So imagine a cube that can only move up or down and the PID controller is controlling an upward force against gravity and we want it to hover at a certain height. P is the power, it's responsible for the majority of upward force. D is the damper, it wants to stop all movement, it's responsible for killing oscillations. I is intelligent, it'll make the small adjustments that P and D can't do, namely without I the cube will never quite get to the desired height. This is definitely not engineering, so definitely not an engineer's way of thinking about it but I think it's very useful.

[@bloodyl_uk]

Exactly what I saw in watching this video, cheers.

[@victornpb]

Yeah I used it in software a few times as well.

[@iamjimgroth]

uzimonkey I use this for AI controllers. :)

[@justinbouchard]

i love principles that can be applied to mass amounts of different applications absolutely fabulous

[@TheHuesSciTech]

I think you missed the main point of the D term. If your oven has a lot of thermal mass, *both* the P and the I terms will suffer from overshoot. The D term is very specifically the anti-overshoot term; because it's the only one "smart" enough to see "the oven is below the target temperature, but nevertheless I'm going to vote *against* putting in more effort because it is trending up so fast that I can see it might overshoot soon". On the flip side though, it's refreshing to see a video that doesn't claim/imply that PID controllers are perfect in all scenarios; thank you for mentioning bang-bang controllers.

[@ramueller11]

That's a good point. To go futher PID terms could be considered the present, past and future terms, respectively.

[@qcnck2776]

ramueller: Thanks, that is a great way to look at it

[@JRush374]

TheHue's SciTech this is what I was thinking too. The D term would take the current position and its derivative and use that to calculate an approximation for a future position. If it's getting close to the set point but is still pushing hard towards that set point, the D term puts on the brakes to help prevent overshoot. Then in the next time step it calculates the approximation again and adjusts accordingly.

[@Mr.Newlove]

Great video, and contrary to other comments; keep the math or even have more of it. But with some people talking about including electronics, maybe you could have used a small heater element and an Arduino to demonstrate real-time tuning? Or even auto-tuning like many 3d printers use for their heaters. In the end a strong foundation in the theory followed by a good practical example of the implimentation is a great way to drive things home.

[@itzlagana]

maybe steal a vid of an inverted double pendulum

[@qcnck2776]

I second that, esp using an Arduino. Great vid, many thanks

[@wgm-en2gx]

Does anyone know of a good simulator of an over or inverted pendulum in which you could try applying a PID controller to?

[@wgm-en2gx]

Can you post links in YT comments? This might be a good simulation. robotic-controls.com/static/inverted-pendulum/ If the link does come through google robotic-controls inverted-pendulum. There is a link in the article for the simulator.

[@metheone4]

why not?YT=Google and links are not copyright protected,soooo....

[@calabrese1531]

Very easy to follow, clear and fun explanation of what PID Theory is. Thank you David. Looking forward for the continuation of this topic. Good job!

[@kevyelyod1211]

I look forward to more control theory videos.

[@adamsfusion]

This was so cool and so enlightening. I'm just a hobbyist, but I love diving into the work of degreed professionals and seeing what kinds of things they learned in school, and these EEVacademy courses are like a treasure trove of direct info as well as info to look up later.

[@coje4219]

Great video, very informative and well done 🤗 looking forward for the rest of the series!

[@krgtim]

I hesitated to click on this video because I usually watch Dave's EEVBlog videos to slowly fall asleep, but now that I have found some time to watch it out of my usual schedule I have to say I really liked it for the educational aspect. Please make more videos like this one! Thanks! Oh and nice touch with the picture at the end. That made me actually chuckle a little bit.

[@pacsmile]

What a nice way to explain this, i wish my teachers at college taught me like this, keep up the good work!

[@Axelios]

Nice PID video. I thought I already knew everything about PID but you taught me several things I hadn't realized or come across. It was worth the 27 minutes!

[@peoplethesedaysberetarded]

Greetings. One immediate recommendation: please don't wait until 5 minutes in next time to define your main acronym. Common practice is something like this: "Proportional Integral Derivative (PID) Controllers Explained." Right there in the title or title slide. Boom. Done. This isn't a slight against you or hate-mail, just a touch-stone to one common recommendation of providing clear technical writing.

[@maniacalcactus4705]

Holy crap this is the boring part of the series?!? I can't wait for the rest this was incredibly interesting

[@ficolas2]

Maniacal Cactus my thoughts exactly

[@iwtommo]

Have a look at "Teaching old motors new tricks" for some real juicy control system nerdiness

[@y.z.6517]

I read this topic before, but this video makes it much easier.

[@jeremyhall7259]

An actual good video on PID controllers, FINALLY! I have been trying to learn these for years!

[@vehasmaa]

Great video and one of most clear explanation of PID control i have seen.

[@colinterry7261]

Hey! I'm working through my Electrical Engineering degree. I thought this was honestly pretty good. I appreciate the layman explanations of control theory. I am actually taking a controls class soon, so this makes me feel better about that class. There was a bit of rambling and bouncing around, but that's fine. I do that when I explain things to newer students, lol. I also appreciate the math. It's nice to see application, so to speak, rather than just concepts. Keep up the good work! I look forward to more videos on this topic!!!

[@billmoran3812]

Excellent! Excellent! Excellent! I learned basic control theory in college over 40 years ago. It was hard to understand just the theory. I've worked with PID controllers ranging from mechanical analog to fully digital controls for the past few decades. The best way to understand tuning is to do it hands on. It gives you a feel for the dynamics of the process and the amount of hysteresis in the loop. I can't wait to see the inverted pendulum project. This is incredible content. Well done!

[@scalcon1]

Really enjoyed the video, keep up the great work. Looking forward for more control videos.

[@0ADVISOR0]

Awesome Info about pid loops! I was just tuning my quadcopter and reading about pid's and now you uploaded more Info, cool thx =)

[@NilsRohwer]

Great video, thanks! I first saw them in flight controllers for racing drones. There you have to tune your PID's and see the results immediately! Now I really understand how and why. With the drones the P is the responsiveness of the sticks in relation to the drones movement. You want it as high as possible, the I is the drones ability to hold the angle you set it at while flying, and the D is used to dampen oscillations from too high P, however it does make the drones more sluggish. As you said, D resists change, makes sense. Tuning those quadracopters is an art, a blend of snappy controls and smooth video. I really enjoyed this!

[@Audio_Simon]

David2 brilliant video, just the right balance of explanation in each area for me :) Looking forward to the physical example.

[@johalun]

Great video, thanks! Looking forward to the next one.

[@16baad]

Excellent series, Keep it up, I am waiting for more of these EEVacademy videos

[@JonathanDFielding]

Thank you! I took control theory in school but this really helped to understand the PID controller much better.

[@KX36]

So refreshing to see something about PID controllers on KZbin that isn't just tuning by guessing random numbers until the steady state looks OK and never checking the step response which always ends up massively overdamped (like orders of magnitude slower than it could have been).

[@Liamtronix]

Great video! I was just thinking about learning about this and then this vid came out. Perfect timing!

[@Bl00drav3nz]

Thanks David, really interesting topic and I'm looking forward to the next video! :D

[@cosmicmatrix6238]

OMG i'm just a few minutes into this and it's AMAZING good on ya mate

[@lasersimonjohnson]

I spent alot of my career coding PID loops in PLCs. Good video David :)

[@amd64online]

Theory was great to follow alongside, looking forward to the practical.

[@avejst]

Thanks for sharing 😀👍 happy new year to you and Dave

[@peterdkay]

Excellent presentation that gives you a good "feel" without maths. Look forward to next viseo

[@lloydrmc]

Truly brilliant presentation. Relating the equations/terms to the graphs made it understandable to people like me.

[@samgab]

Thanks for your efforts. It would be cool to see this PID info from the point of view of model quadcopters, as PIDs, and tuning PIDs are a huge thing with getting rc model quadcopters working properly.

[@Hasitier]

I like this kind of videos. And you are getting better from video to video. Go on with the great work Dave 2!

[@cveliz_]

Nice video, very well explained. Thank you David

[@DavidLightman]

wow that was extremely interesting!, will look more into that, and looking forward for the next one, thank you!.

[@jwilliams8210]

David, nice job balancing examples and theory.

[@joaovoltani5857]

The best video of the series so far, good job David!

[@davidledger5941]

Thankyou!

[@xanderlander8989]

Really good video! Interested in the inverted pendulum robot design, component selection, and build. Also excited for tuning the little guy. I've watched several people in my university try to build these for fun or for a class, but they never preformed very well.

[@alimmi9]

Thanks alot! I needed exactly this video! Please continue :)

[@metaforest]

Years ago, I developed several user-content 'toys' in Linden Labs' SecondLife that use PID controllers to simulate 3-D tracking behaviors and in one case, a very realistic tire-swing within the environment. It was fun to see this video and revisit my own experience in developing and tuning a PID controller in that context.

[@anishsarkar120]

love the video dave2 as i am studting control engiuneering in uni and you also covered the topic and no mistakes to spot

[@Mr321ruben]

Thanks, it is a very fresh way to explain the concepts. I am less lost with this explanation I think I am going though a good path

[@mrkattm]

Nice job, Controls was my elected concentration as an undergrad EE student until they introduced the State Space method at which time I changed to digital and computer design, a choice I regret. I am looking forward to this series, keep up the good work.

[@davidannett3322]

You're a fantastic presenter! So detailed and engaging!

[@Mr321ruben]

I was like in a total dark room, and now there is a ray of light. Thanks a lot Bro.

[@MkmeOrg]

Very well done. Not an easy topic to explain but hugely useful and widely utilized. Few robotics or flight controllers out there not using PID control.

[@alekseydudko6961]

Great video! Thanks Dave!

[@jb3757]

loved it, simple, clear, and to the point

[@AmRadPodcast]

Nicely presented.

[@captdrsam7773]

Thanks.one of the best explanation .I like the way you combine mathematics together with the actual thing. It really make sense to me, better understanding since I am only good at math but not so to relate it with the actual thing. Once again thank you so much for your fantastic effort to teach us. God bless you Sir.

[@fanest_norfar]

Just the other day i said to myself that i have to look at theory behind PID again since i need to do some regulation and here u come with this video - just perfect :D.

[@chromerims]

Valuable, informative and helpful content👍. Thank you.

[@ZPositive]

Awesome video. I'm stoked to see the pendulum bot take shape! And yes, please keep the math in there.

[@Rost1337]

Great mix of math and examples! Keep it up.

[@TheBigBigBlues]

Great video David, well explained.

[@s.campos9682]

Absolutely great presentation and gace me a further understanding

[@jcobnl]

Great video. I hardly understood how these kind of controllers work, like ambient room temperature controllers or a cruise control system, and how they deal with overshoot. Until now.

[@bacawaka2813]

Awesome! I've taken a controls course before but I never learned the Ziegler-Nichols method. In fact, we never actually touched tuning other than using a given transfer function and finding the corresponding PID values by using a root locus. The major issue is that you have to get the appropriate model first then convert to a transfer function which is already a lot of math. Then you can finally get the transfer function to find the PID values which, in most cases only gets you in the ballpark of the system response you desire. Even then there is trial and error involved at the end to get it dialed in to that response.

[@viodel8032]

Many thanks for this amazing video. Best wishes!

[@davidabineri908]

More like this please, perhaps adding an actual device/program to demonstrate the concepts in context. Very good, clear explanations. Thanks!

[@AmyAndrewAdventures]

Thank you!! Excellent video!!

[@adithyaa1]

Excellent video. Thanks

[@dardosordi]

Great Video, David, much better presentation too, you are getting better every time, seems like you were tuning your constants...

[@uwezimmermann5427]

Absolutely a nice video - it started a bit rough, but once David got into the flow, it became very clear and nice to follow. When explaining the I-part, you should perhaps also have shown the actual "temperature" or state of the oven instead of just the error. You could have combined the two in a single graph where you had shown a line for the setpoint and drawn the error between the setpoint and the actual state. YES, keep the math, it is necessary here!

[@matheoml]

Awesome explanations!

[@mysomervda]

I liked this explanation. Good job David.

[@CaliReef]

Loved it, would like to see more of the math, and maybe a demostration implementing the control theory. 3rd year EE

[@nukularpictures]

woot and then you havent had a lecture about that? After 3 years?

[@CaliReef]

nukularpictures taking it next semester actually.

[@nukularpictures]

Wow that is late. I had it in the 3rd and 4th semester. But yeah its a really interesting topic, especially with the more advanced controllers and fuzzy control. Its a good choice :)

[@Bigelowbrook]

What's the whiteboard software that you're using? Thanks!

[@davidledger5941]

Drawboard, from the windows store.

[@Bigelowbrook]

Thanks!

[@kiranchinnam4341]

David Ledger On the Surface?

[@Donaldo]

I find the undrawing of the pen stroke really distracting

[@mandomonica]

Best explanation ever! Thank you!

[@toastrecon]

Very helpful, thank you!

[@91722854]

Ever since I learned Control, I see it everywhere, we are all in harmony because of the feedback and control of our systems with Brain OS, mine currently have 1024 bit cpu, 4096 TeraByte of RAM, but need an upgrade to my soft drive

[@oliss10]

This is my line of work :) Measuring instruments, controllers and process valves :) and PLC's naturally :)

[@radoslavradoslavov3528]

If I can't get this explanation I can't get any other. Thank you very much!

[@johnsnow5305]

I don't know how this was boring lol. I guess I just like learning, so I found it interesting. I love learning how math works in the 'real world' - I die trying to learn math purely for math's sake. So something like a PID controller is perfect for me - shows how you can use math in the real world to achieve things you want. I'm glad you included the animation at the end - it definitely helps to see the effects of variable changes in real time like that. I hope you guys do a tear-down or something of a typical PID controller during this series. I would love to learn how the circuits / components work together to make this math happen.

[@sher.5027]

Thanks for this video.

[@omar7amdi]

Thanks and I hope the other parts are better. As a matter of fact you presented more information than the others who talked about PID. PID is vague subject presented by books and many instructors.

[@DingoAteMeBaby]

Finally a simple PID controller explanation!

[@lasersbee]

Love the explanations of PID tuning... Well done Dave#2.. An electronic/mechanical setup with demonstration would be an added feature. Could you possibly put a link in the description to the Animated PID Graph ?

[@sloMoses]

Well done. Thank you.

[@blickberg8404]

Awesome video.

[@tzampini]

Excellent explanation of PID control. Thanks.

[@davidledger5941]

Thankyou!

[@johnpossum556]

feedback: Screech your voice like Dave, it throws my thinking off. Seriously, Dave, that was an excellent vid on digital data logic sheets. I went to college for Avionics tech and that was above and beyond. That is the kind of content I really enjoy watching from you. Something that furthers my understanding of a topic I already love.

[@TripleJ85]

Nice one David - clear and concise.. I wish I had resources like this when I was a student - maybe I would have learned more and played less poker :/

[@ajj7794]

WHERE is the NEXT VIDEO. I LOVE your method of teaching. pls do more. i have done courses in control but i feel enlighted each time i watch great videos as this really show how simple PID control theory is. i still am not very confided on the propotional part but i have a good idea as its just an offset constant but still i would like to improve my understanding of it furthur and thus seeing ure example with an actual system will be veyr useful. i am very greatful for this. MANY THANKS

[@spikeyeddy]

great explanation

[@TheDuckofDoom.]

Good effort. You forgot the essential role of the delay in the control feedback loop, without this system delay there would be no need for PID controllers. I wish I could recall the website I found many years ago(~15) explaining PID control, it was very spot on, covered the math in a reasonable manor(especially the strengths of the three components at different levels of initial error) and it had some very nice example graphs.

[@davidledger5941]

Delay isn't the only reason for PID controllers, infact in many system models it can be ignored. Delay is very significant in systems involving heating and cooling and I suppose I did talk about that so maybe should have mentioned it.

[@eziosoft]

More videos like this please !

[@CanDoo321]

Thank you David.

[@florentinosanchez3969]

Thank you so much for making It

[@Landrew0]

Excellent explanation, much better than Dave, who can make the simplest concept incomprehensible by over-explaining it to death.

[@JGnLAU8OAWF6]

Do more videos on control theory, that stuff is amazing.

[@davidledger5941]

Thanks, will be!

[@SaurabhGavali]

Overall a really helpful video on PID controller...can u also discuss Offset in P-only control..I found that P-only offset in ur video is implicitly explained at the end

[@revealingfacts4all]

Excellent video. I develop software for autonomous vehicles in the agricultural industry. Our controls engineers use simulink to develop their "models" and I develop the wrapper code as we call it to feed the model with data. Our controls engineers are always tuning the system. Our systems controls a steering valve for an auto guidance application. This video filled in some gaps for me. Now I know what my controls engineers are really doing lol...

[@davidledger5941]

Glad to help :)

[@mingijeong3956]

Thank you for your great video. Should y-axis of 17:42 part graph be value (set point and present value) not error? Since, it does not make sense to me that we try to set the error at a certain stable value.

[@tobyccw]

Great video, would you help me to understand. if i do a bode plot on the " treadmill "analogy 1.what is the frequency input? 2. what is the gain of the bode plot in this case? is it the same as PID gain?

[@peterg.8245]

What's next a discussion of root locus? 😏 Great video, my EE specialty was control theory out of a very very plain navy book with no graphics, circa 2005. Used PID controllers for temperature control of large incinerators, >100 MBTU thermal oxidizers, down to small ovens for refractory tile, only 4 pallets or around 2000lb to dry them out before installation, they still had to be cured in the furnace/thermal oxidizers/flare.

[@MellexLabs]

This is an excellent starting video... I think you need to show the math a long side an application which I think will home in the concepts better... I like the way you presented this please do more on control theory...