- Видео 56
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Ben Dickinson
Добавлен 18 янв 2011
This channel is dedicated to education in the fields of guidance and control. Content will range from undergraduate to graduate-level university topics. Specific lessons range from the basic to advanced, the common to obscure, and the theory to application. Students, engineers, researchers, program managers, or those just curious about GN&C will find value in this channel.
X-15 Stability Augmentation System | Yar Control | 6DOF Flight Simulation Tutorial - Section 3.1
The X-15 operates over a wide range of flight conditions leading to underdamped body oscillation and poor handling qualities. The pilot relies on a stability augmentation system (SAS) to artifically dampen rigid body modes, thereby reduce their workload and focus on the mission.
This lesson focuses on stability augmentation of the X15. Assisted by our full 6DOF flight dynamic simulation, we will answer:
1. What is a SAS?
2. How can we determine the SAS architecture for X15?
3. How can we use a SAS to decouple roll due to yaw?
4. What is the effect of the X-15 SAS on roll, pitch, and yaw maneuvers?
Access this Lesson and More:
www.LearnGandC.com
Support the Channel for 5 Bucks = Get the Codes
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This lesson focuses on stability augmentation of the X15. Assisted by our full 6DOF flight dynamic simulation, we will answer:
1. What is a SAS?
2. How can we determine the SAS architecture for X15?
3. How can we use a SAS to decouple roll due to yaw?
4. What is the effect of the X-15 SAS on roll, pitch, and yaw maneuvers?
Access this Lesson and More:
www.LearnGandC.com
Support the Channel for 5 Bucks = Get the Codes
w...
Просмотров: 1 604
Видео
X-15 Space Plane - A Review for 6DOF Model Development | Flight Simulation Tutorial - Section 2.1
Просмотров 1,3 тыс.4 месяца назад
This lesson is tailored toward 6-DOF model development of the X-15 space plane. Our goal is to provide a concise overview of the relevant systems to a full rigid body flight dynamic model. Topics include the X-15 mission, outer mold line, control surfaces, reaction control system, propulsion, air data systems, inertial flight data system (navigation system), stability augmentation system, and t...
Flying Bricks | 6-DOF Verification | Aerodynamic Damping | Flight Simulation Tutorial | Section 1.5
Просмотров 1,6 тыс.5 месяцев назад
Verified flight simulation is essential for accurately modeling aircraft dynamics. This lesson focuses on partially verifying a Python-based simulation through three check cases: a dragless sphere, a tumbling brick without aerodynamics, and a tumbling brick with aerodynamic damping. Each case is validated against benchmark data from the NASA Engineering and Safety Center. We connect the Python ...
Navigation Equations | Atmosphere | Aerodynamics | Angle of Attack/Sideslip | Flight Sim - Sec 1.4
Просмотров 1,7 тыс.6 месяцев назад
Here we add the final components to create a complete flight simulation. Building off Section 1.3, we will explain the navigation equations, incorporate an atmospheric model, explain relative velocity, angle of attack, and angle of side slip. We also incorporate an aerodynamic model of a sphere with the body to wind axes transformation. These additions are coded in our Python simulation. The ne...
Aircraft Euler Kinematics (Attitude) Simulation in Python - Flight Simulation Tutorial - Section 1.3
Просмотров 3,5 тыс.7 месяцев назад
The goal of this lesson is to understand how to model aircraft attitude from angular rates. Toward this, we review Euler angles, Euler angular rates and how they differ from body resolved angular rates, the Euler kinematic equations, and coding the Euler kinematics in Python coupled to 6-DOF dynamics. This lesson establishes a working bare-bones simulation with aircraft governing equations. To ...
Aircraft 6-DOF Equations and Coding in Python - Aircraft Flight Simulation Tutorial - Section 1.2
Просмотров 7 тыс.8 месяцев назад
In this lesson, we describe the aircraft six degree of freedom equations of motion. This includes their reference frames and coordinate systems, oblate earth and flat-earth approximation, the 6-DOF vector and scalar forms, variable nomenclature, the basic structure of the simulation, and coding a main driver, the 6-DOF equations, and a numerical integrator in Python. This is the second lesson o...
Six Degree of Freedom 6-DOF Aircraft Flight Simulation Tutorial - Introduction - Section 1.1
Просмотров 4,6 тыс.9 месяцев назад
This video introduces the development of an aircraft flight simulation, its potential uses, components, and considerations. This is the first lesson in a tutorial series that will walk through developing and coding a full 6-DOF aircraft flight simulation. References: Note: If you purchase Stevens and Lewis' book from the link below, I am provided a small commission to support the channel while ...
Probability & Statistics of Noisy Signals for Kalman Filters, Guidance Fundamentals II, Section 1.2
Просмотров 62910 месяцев назад
In this lesson, we develop fundamental probability and statistical concepts for working with noisy signals in stochastic control and Kalman filter design. Topics include: noisy signal characterization, sample space, mean, expected value, variance, stationary processes, covariance, the covariance matrix, the joint moment matrix, the autocorrelation matrix, uniform distributions, and gaussian dis...
Time to Go Estimation - Guidance Fundamentals II - Section 1.1
Просмотров 1,2 тыс.11 месяцев назад
In this 40 minute introduction, you'll learn: why time to go is important, how basic time to go estimation methods found in textbooks are derived, how the accuracy of these methods compare, assumptions and limitations of these methods, and how time to go accuracy affects miss distance. In the process, we review and apply linearized augmented proportional navigation, which depends on zero effort...
Automatic Flare Path Control - Flight Control Fundamentals - Section 1.6.5
Просмотров 2,2 тыс.Год назад
The objective of the flare path is to reduce aircraft rate of descent for a safe touchdown. In this lesson, an exponential rate of descent model is derived and incorporated in a flare path control loop as part of an automatic landing system. Lesson topics include the development of the closed loop airspeed and pitch controlled aircraft, altitude modeling, flare path control development, and sim...
Guidance Fundamentals - The Self-Guided Course
Просмотров 1,4 тыс.Год назад
This self-guided course is an organized framework to systematically learn guidance fundamentals. It is built off the openly available Guidance Fundamentals series and offered as a digital package for download. The package contains: 1. A self-guided schedule to step you through the course, 2. All lesson videos in .mp4 format, 3. All slides, 4. All codes, and 5. Problem sets and their solutions. ...
Aircraft Glide Path Control - Flight Control Fundamentals - Section 1.6.4
Просмотров 2,2 тыс.Год назад
In this lesson we implemented aircraft glide path control, involving airspeed, glide slope, and pitch angle control loops are applied to the longitudinal dynamics of an aircraft to enable commanded tracking of glide slope and airspeed. We derive the appropriate models for control and establish the control architectures. The multi-loop system is tuned systematically with root locus and step resp...
Aircraft Airspeed Control with Lead Compensation - Flight Control Fundamentals - Section 1.6.3
Просмотров 1,1 тыс.Год назад
To improve automatic landing control, we develop a proportional integral airspeed control system. We linearize the nonlinear aircraft equations of motion around the glide slope, resulting in an LTI system for control. However, the closed-loop system's performance is limited by a 5-second engine response time. To address this, we introduce a lead compensator in the feedback loop, replacing the s...
Pitch Tracking Control with Lead Compensation - Flight Control Fundamentals - Section 1.6.2
Просмотров 1,2 тыс.Год назад
In this lesson a lead compensator is applied to improve the pitch angle tracking response of a transport aircraft. The nonlinear longitudinal aircraft equations of motion are linearized about the glide slope, providing an LTI system for control. The open loop dynamics shows a zero near the origin, which attracts the closed loop pitch pole related to tracking rise time. Thus, the zero limits clo...
How to Transform the Lead/Lag Compensator into State Space Form - Quick Concepts in Control 3
Просмотров 1,5 тыс.Год назад
How to Transform the Lead/Lag Compensator into State Space Form - Quick Concepts in Control 3
Trim for Autopilot Development - Flight Control Fundamentals - Section 1.7
Просмотров 1,8 тыс.Год назад
Trim for Autopilot Development - Flight Control Fundamentals - Section 1.7
Automatic Aircraft Landing Introduction: Control from Glide Path to Flare Path - Section 1.6.1
Просмотров 1,6 тыс.Год назад
Automatic Aircraft Landing Introduction: Control from Glide Path to Flare Path - Section 1.6.1
How Transfer Function Zeros Affect Transient Response - Quick Concepts in Control 2
Просмотров 6 тыс.Год назад
How Transfer Function Zeros Affect Transient Response - Quick Concepts in Control 2
Acceleration Tracking Control - Flight Control Fundamentals - Section 1.5
Просмотров 3 тыс.Год назад
Acceleration Tracking Control - Flight Control Fundamentals - Section 1.5
Pitch Rate Tracking Architecture, Tuning, and Effects - Flight Control Fundamentals - Section 1.4
Просмотров 5 тыс.Год назад
Pitch Rate Tracking Architecture, Tuning, and Effects - Flight Control Fundamentals - Section 1.4
Closed Loop Transfer Function - Quick Concepts in Controls #1
Просмотров 3 тыс.2 года назад
Closed Loop Transfer Function - Quick Concepts in Controls #1
Artificial Damping - Flight Control Fundamentals - Section 1.3
Просмотров 3,4 тыс.2 года назад
Artificial Damping - Flight Control Fundamentals - Section 1.3
Pitch Autopilot and Tuning- Flight Control Fundamentals - Section 1.2 - Rev 2
Просмотров 10 тыс.2 года назад
Pitch Autopilot and Tuning- Flight Control Fundamentals - Section 1.2 - Rev 2
Autopilot Introduction - Flight Control Fundamentals Section - 1.1
Просмотров 7 тыс.2 года назад
Autopilot Introduction - Flight Control Fundamentals Section - 1.1
How to Plot and Animate Missile Trajectories in MATLAB - Guidance Fundamentals - Appendix B
Просмотров 6 тыс.2 года назад
How to Plot and Animate Missile Trajectories in MATLAB - Guidance Fundamentals - Appendix B
Lyapunov Stability and Linear Quadratic Regulator (LQR) Stability Proof
Просмотров 1,7 тыс.2 года назад
Lyapunov Stability and Linear Quadratic Regulator (LQR) Stability Proof
Augmented vs True Proportional Navigation (3/3) - Guidance from Optimal Control - Section 2 Module 3
Просмотров 1,8 тыс.2 года назад
Augmented vs True Proportional Navigation (3/3) - Guidance from Optimal Control - Section 2 Module 3
Augmented Proportional Navigation Part 2/3 - Guidance from Optimal Control - Section 2 Module 2
Просмотров 1,2 тыс.2 года назад
Augmented Proportional Navigation Part 2/3 - Guidance from Optimal Control - Section 2 Module 2
Augmented Proportional Navigation Part 1/3 - Guidance from Optimal Control - Section 2 Module 1
Просмотров 2 тыс.2 года назад
Augmented Proportional Navigation Part 1/3 - Guidance from Optimal Control - Section 2 Module 1
Stability Margins from Nyquist Diagram - Classical Feedback Control - Section 2 Module 1
Просмотров 2,3 тыс.2 года назад
Stability Margins from Nyquist Diagram - Classical Feedback Control - Section 2 Module 1
Hi ben, i am trying to implement this on matlab. I am using the transfer fucntion of plant and actuator as given in your video and plotting the root locus of it. For my case the short period modes crosses imaginary axis at gain value of3. Can you guide me as in your case it doesn't hit the imaginary axis before 170? Thanks
Hmmm.... what about your actuator pole? If it's too slow then it can cause instability at low gain.
@@LearnGandC Hi Ben, the actuator pole is at the same place (s=-4) as indicated in the video
Ben Dickinson, you are my savior!!!
Hey there, it's great to hear the lesson is coming in handy! Thanks for watching
Ben, this is amazing! You compressed a lot of information here and some of the steps/conclusions are not entirely clear to me. Would you be able to help me with identifying resources which I could use to study what you present in your video? Specifically, I would like to understand (1) how you interpret the plot of root loci on the complex plane for the phugoid and short-term modes and read about "feedback control architecture" - you mention it when analyzing the closed-loop system response as a function of K.
Thank you! I'd recommend Blakelock, Automatic Control of Aircraft and Missiles. The 1st edition is fine and much cheaper, but the 2nd edition is better if you can find it.
How will get python code
Hello Sankalp, as you have found, you can access the code from my Patreon page. Thank you for subscribing!!!
@12:43 why t_go cant be the left calculation? (with the + determinata)
Ah, because the left answer would provide a negative tgo estimate. Examine the numerator terms to observe this.
@@LearnGandC First of all, thank you so much for your posts and videos. They are incredibly informative and a true pleasure to watch! but i dont get why t_go is negative on the left. for example v=-10 A=1 R=32 the sqrt((-10)^2-2*1*32)=sqrt(36)=6 in this case the left value is -(-10)+6=16 and the right value is -(-10)-6=4 both postive
Of course, glad you like the content! Note closing velocity is positive when the bodies are approaching each other. Also, while there are exceptions as you may have found, that solution provides negative values for a relevant range of parameter values.
thanks, Ben, these video help me a lot
No problem! Thanks for watching!
can you explain the selection of 7.5 factor for the lead compensator (10:16)? In the previous video you set it to 4 when the compensator was (s+0.22)/(s+0.88) to make its gain 1. Now following the same logic the factor should be 20. What am I missing?
Ok, had to do a little investigation. It's to make a steady state gain of 1, but the transfer function is not correctly listed. It actually has a pole at 1.5. You can find this on my Patreon post (thanks for subscribing) at the link below. Go into the driver PI_Control_of_Airspeed and then look at Part G where the lead compensator is specified. Thanks for watching and the question! www.patreon.com/posts/airspeed-control-85847981?Link&
@@LearnGandC OK now I understand. The gain of 7.5 is for the pole at 1.5 that you showed as a compromise after the pole at 4 required too much control effort (risk of thrust saturation).
Thank you for this great series of videos. I have seen now 1.6.1 and I think this video should come last. Video number 11 and 12 in the current playlist should come before it (you can add the number 1.6.4 & 1.6.5 to their thumbnail to make it more clear).
Thanks for the suggestions! I agree and will update the playlist.
minor mistake at 11:45 you encircle the controller transfer function and include the actuator which is part of the plant
Ah thanks for catching that. I plan to update the lesson in the near future as a second revision.
Hi...what is the best book for guidance plz
I'd recommend Paul Zarchan's book. You can find it on my list of recommended texts: learngandc.com/recommended-texts
PN with Zero Effort Miss is linearized PN, it is not a non-linear general PN, is that correct? So we can get criteria designs upon it, not a real implementation.
Not necessarily. For example, linear analysis and application of linear control methods has been effective in aircraft control for decades!
At 7:43, it looks like true PN requires less acceleration than pure PN. Is that a definite conclusion from this section? In other words, true PN overcomes pure PN in terms of acceleration requirements. Is that why Dr.Zarchan did explain pure PN in his book? I mean it needs high ap
I don't believe this is a general conclusion that can be drawn (Pure requires more ap than True). Pure ap is proportional to Vp while True is proportional to Vc. In this example, Vc > Vp, and I believe this is in part why for a given N, ap-True < ap-Pure. I don't know why Zarchan focused on TPN. His book is already long enough, actually now two volumes, so perhaps it's a brevity thing.
From the comparison table between true and pure in control effort, it looks like true PN has less control effort with optimal N for each algorithm. Does it mean that true overcomes pure from control effort perspective? or is that only for the heading error case? Can be generalized to target acceleration case? Also, others say that the forward velocity variation requirement in true PN leads to a relatively large control effort requirement over pure, or should the implementer ignore that component?
Great series of videos. This video specifically is less clear (and less important) than the other videos in the series. Note that the order of the playlist is wrong - this should be that last video in the playlist.
Thanks, based on your comment, I've reordered the playlist so they are now in order 2.1 to 2.6!
in the code at 18:58, shouldn't w_over_v be called w_over_u?
Yes, you are correct. Thanks for pointing this out. I'll update the errata in the description. Although the name should be w_over_u, it's actually implemented correctly.
Excellent tutorial! My checks for cases 1,2, and 3 pass successfully. However, when I test check case 4 (C.1.4), which adds a constant C_d to the sphere, I note incorrect results for position x and y in NED (they should remain zero, but instead become non-zero). I believe I've traced the error to the calculation of external forces F{x,y,z}_b_kgmps2, which I think might be incorrect from previous videos. Is this true?
Thanks. Not to my knowledge, I was able to verify against the check cases. Are you sure your initial conditions are consistent? Note, pitch angle is set to -90 degrees so that the brick accelerates in the positve x-direction.
Good evening Sir please How the auto pilote maintain Pitch attitude +2,5° of Boeing and Airbus at flight level 40000 ft speed 480 kts without Switch command on the MCP.
Another Banger of a lecture by Ben! Doesn't get any better than these honestly. Appreciate you mate.
My pleasure! Thank you!
Thanks for such a nice lecture. will the proportional coefficients once set, be valid/effective for all flight speeds to provide stability? Is it beneficial to use Integral and differential coefficients as well in PID control?
Your welcome! One set of gains at all conditions will be better than no gains, but it's not ideal. About any flight condition, there will be a set of gains that produces the ideal behavior. So, the pilot can adjust with knobs. A gain-scheduled SAS would be the next step. For integral control, it could certainly by used a in control augmentation system (CAS) where there's an outer loop to enforce tracking of the pilot-commanded variable. Derivative control could help dampen rates more quickly, but of course there's the risk of amplifying noise through the derivative. Proportional control is a simple solution that apparently met requirements based on the number of successful flights. So from an overall experimental space plane program perspective, it's possibly the best approach for its purpose.
Ben, those errors which you mention at the end of the video: you found those *prior* to recording this lesson, am I correct? That is, you are telling us that your original code had errors, you attempted the verification, you found discrepancies, looked for errors and fixed them, and then finally recorded the lesson with fixed code. Is that correct?
Yes, that's correct! I did a poll and people wanted insight into the issues found when developing the simulation.
@@LearnGandC got it, thank you. I definitely appreciate that insight, it is consistent with my own experience, I must say, quite unfortunately. I asked because I wasn't sure if I was supposed to look deeper into the plots to see minuscule differences between lines in the plot. Great job by the way, I'm enjoying those videos a great deal.
Hi Ben, on the MCP of airbus or Boeing don't existe Switch to commande the pitch attitude,How the Auto Pilote maintien +2,5° in cruise i. want to know the loop
Hello there. Unfortunately I don't have specific insight into Boeing or Airbus autopilot architecture. However, pitch command tracking controllers have fundamental PI architectures. For example, one could implement integral control on pitch angle error and proportional control on pitch rate for artificial damping. This makes use of navigation and IMU data which should be part of the avionics of modern aircraft. My series on longitudinal flight control (see www.learngandc.com) covers the architecture and tuning of basic controllers like the pitch tracking controller.
Very good
are you saying that we assume that earth is flat so the math can work so we can fly ?
It's a valid approximation for aircraft modeling and simulation when speed and distance is limited. For accurate prediction of aircraft flight at high speed or over longer distances, we must account for the oblate and rotating earth.
How many total video lessons is this series going to have?
Hello, at least two more. There's one about initial model development (coming soon) and the one where a more comprehensive model is developed. Over time, new parts of the simulation will likely be added and this simulation will be used for flight control lessons in other series.
I wish I have found this channel during my masters, but better late than never.
Haha, true. More lessons coming soon.
This is awesome, very clear explanation
Thank you!
This is far and away the best video a student seeking to learn how to simulate aircraft EOMs could watch. I'm a senior at the University of Illinois in Aerospace Engineering and I work on a team funded by a SIIP grant to develop simulation software that can accurately simulate flights and other aerospace-related physics. I have been trying to learn the mathematics behind the EOMs and this was just what I needed! Thank you so much, I am looking forward to your future content.
That's great feedback, thank you! It's been a while, but the content for my next lesson is coming to fruition. It's derving a flight dynamic model of the X-15 spaceplane from the literature and simulating its dynamic response. Be sure to check out the errata of this lesson (and my other lessons) in the description below. How many bugs/errors are left after one is found? n-1
god i love the internet, thank u ben
Haha, you're welcome.
One question, what methods are used to measure and estimate the acceleration of the target to be fed forward to the APNG?
My simulation was coming up as unstable. I removed the minus sign and everything was ok
Great, that issue has plagued us all at some point.
Hello. Greatly enjoying the videos and hope you keep posting. However, I would like to note a mistake in one of the formulas you displayed. At approximately 15:55 when you show the Navigation Equations, the first element of the first row in the matrix is wrong. You post it as cos(theta)*cos(phi) which is incorrect. It should be cos(theta) *cos(psi). I believe this is just a typo as you carried out your coordinate transformations correctly everywhere else. Just for reference, this can be found on page 110 of Aircraft Control and Simulation by Stevens and Lewis (2nd Edition) Cheers
Good catch! Yes, this actually carried over to my sim and caused me several hours of troubleshooting before I found it. I'll post an errata for this lesson. Thanks for watching!
I honestly never thought about a compensator in state space , I always did a z transform and implement the difference equation.
Yes, it's particularly useful when we have a continuous time simulation.
Absolute Gold mine , thank you very much sir .
Glad you like it! Thanks!
Great video! Just wanted to clarify why the omega x linear velocity product is in the rotational equation of motion. Should it not be omega x (J omega) as this is the gyroscopic effect rather than rotational effects on translation.
Thanks for watching! Yes, you are correct. Unfortunately, this is an error. I'll add an errata list to the description. Thanks for catching this mistake.
do you have any videos or know of resources on the lateral component (localizer)?
Hello, I do not have lateral control videos but Stengle has an open online course that may cover it. You can access it at www.learngandc.com. Navigate to Resources/Courses then scroll down. Thanks for watching.
@@LearnGandC thank you!
Sir, thank you for this video. It was so helpful for me to understand the 6DOF baseline. I have a question for code if u don't mind. I think in line 117-118, the variable sign should be negative for Jxz from the formula (-Jxz). I'm not sure if I'm wrong, that's why I wanted to ask. Thank you again.
It's my pleasure. Could you be more specific? For example, the time of the video and the equation with the error in it? Thank you
@@LearnGandC The time is 22:56. When i compare the equation of yaw and code (117 to 120), i notice that there may be a sign discrepancy. In other words, comparing the code and my opinion: dx[5] = -->(in video) ((Jxx_b_kgm2 * (Jxx_b_kgm2 - Jyy_b_kgm2) + Jxz_b_kgm2**2) * p_b_rps * q_b_rps + \ Jxz_b_kgm2 * (Jxx_b_kgm2 - Jyy_b_kgm2 + Jzz_b_kgm2) * q_b_rps * r_b_rps + \ Jxz_b_kgm2 * l_b_kgm2ps2 + \ Jxz_b_kgm2 * n_b_kgm2ps2)/Den -->(photo of formula (my opinion)) ((Jxx_b_kgm2 * (Jxx_b_kgm2 - Jyy_b_kgm2) + Jxz_b_kgm2**2) * p_b_rps * q_b_rps - \ Jxz_b_kgm2 * (Jxx_b_kgm2 - Jyy_b_kgm2 + Jzz_b_kgm2) * q_b_rps * r_b_rps + \ Jxz_b_kgm2 * l_b_kgm2ps2 + \ Jxz_b_kgm2 * n_b_kgm2ps2)/Den
Thanks for letting me know! If I have not added it to the errata, I will do so.
Thank u Ben Sir.
Most welcome!
Is there an additional step required to go from ZEM's lateral acceleration to an angular rate command for a body? Is there a "correct" way of doing this?
Yes, you can directly translate it to flight path angle rate but I have not tried to convert to pitch rate. You may be able to make a PI-coupler between acceleration and q.
Hey Ben, this is a great video, and it's already helped me a lot, but while I've been trying to understand control theory, the variable s has confused me thoroughly. How is s defined? Can I choose whatever value s will take on (I know that it at least holds the value wj where j is the imaginary number)? or is it based directly on my delta e variable at that point in time that I am simulating. I appreciate your help.
A lot of the research I have done into trying to figure this out tells me that omega is the input frequency, but if I am not using discrete time-steps or I just need to figure out what s is when time = 0, I have no idea what I could use to find that value
Hello there, for our purposes s=jw where w is frequency and j is the imaginary number is sufficient, although there is deeper discussion to be had for sure. Note, the frequency domain analysis assumes that the dynamics are only driven by the oscillatory input and that the transients due to a nonzero initial condition have decayed to where they are negligible. The system output is independent of the initial condition at t=0.
@@LearnGandC Thank you, this helps my understanding somewhat, but a more specific question. How exactly do I calculate the frequency based on a control input? Also, how would I go from finally building my P controller to actually being able to simulate the flight of my model over time?
@@LearnGandC Also, is there a way I can access the Octave code that you wrote to do all of this and generate your plots?
For controller tuning and analysis, we often use a combination of frequency and time domain methods. However, for simulation of the controller in the loop with the plant, it's done completely in the time domain.
Ive been studying Zarchan a while, friend just recommended this series so looking forward to seeing your take
Cool, I hope you enjoy it. This largely maps to Chapter 2 in Zarchan, but with a lot more details.
@@LearnGandC that makes sense, I’m into the optimal control stuff now but still interested in the basics as its been a little while since i had time to make good progress lol
Hi ben great work as usual ! i ran the simulation and i got similar results. just a small correction : in the video, you pointed out that the initial separation is 30000ft, whearas in the simulation it is taken to be 40000ft.
You are correct, this is a known error. I'll add it to errata in the description if I have not already. Thank you
Hi ben! Amazing video! The only thing I didnt understand is how to transform the acceleration command into the Z and X acceleration commands relative to the pursuer frame. Any insights?
Hello, to resolve the acceleration command in the body coordinate system, we must transform with the direction cosine matrix that is based on the line of sight angle. See the discussion starting at 12:50.
A320 rated here. I've been messing around with coding for the past few weeks and this gem popped up in my RUclips feed, thank you sir!
That's awesome. Glad you like the video! You can access my whole library for free at www.LearnGandC.com
One of the best if not the best channel on GNC topics on youtube !
Thanks so much!
Wow
My God, who figured all of this out
We stand on the shoulders of many smart people who came before us!
where is code for the sim?
Hello there, codes are available through Patreon. The guidance codes are all the way at the bottom of the list of posts. www.patreon.com/user?u=86359827
7:10 shouldn’t the last equation contain a big M (aka M being Torque/Moment)? As currently shown m is a mass. Great video by the way!
You are correct! I'll update the errata in the description. Thanks for catching that.
18:14 I also noticed that in the flight control section it should be -e i think.
Is there also any way to get s more explicit view of how you did some parts of the process/ calculations. For example when you showed us the equations of motion I wasn’t sure if to treat α as a variable or a constant (trim condition) and if α_T was a variable or constant. I also don’t know what exactly you used as inputs for the Moment/Torque in 7:10. The video is magnificent but some things were skipped such that it is quite hard for me (an enthusiast) to follow/ model by myself with the use of Matlab.
probably the best open source resource I've found on implementing stevens and lewis, invaluable stuff!
Thanks so much! I'm looking forward to getting the next lesson out.
Absolutely invaluable series! I plan to make my own flight simulator in C++ and I'll be using this playlist as guidance. Keep up the good work!
That's awesome! Thanks for watching!!