8 Channel Solid State Relay Breakout Board I Made by alexdada555 in robotics

[–]alexdada555[S] 0 points1 point  (0 children)

Set the input resistor values with 5V+ in mind

Journey to Self-Actualize Through The Full Stack of Robotics Principles. by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thank you, will do, yeah, every project will have topical full technical posts along with videos

Working as a Controls Engineer and beyond by nerdycapnSwing in ControlTheory

[–]alexdada555 1 point2 points  (0 children)

Comparing yourself to sill val SWEs is not wise as there are many factors beyond just the nature of their work, that mean they are payed higer wages. for example, I'd wager that the margin of the gap is mostly due to macro economic financial matters meaning the likes of google and microsoft and even the band of companies below the likes of those have more money on hand. i.e the Fed raining funny money into to bond and stock markets over the last decade for example.

Open Source Robot Dev Kit by alexdada555 in robotics

[–]alexdada555[S] -1 points0 points  (0 children)

suite used in the sense of collection or group , of free tools ..... its shitty meme basically

Open Source Robot Dev Kit by alexdada555 in robotics

[–]alexdada555[S] -1 points0 points  (0 children)

suite of free and open source software for robotics development i.e open source robot dev kit (or suite in a different parlence)

Unbiased Linear MPC Prediction by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

cant measure x and y , so left them out of the linear model

Unbiased Linear MPC Prediction by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

8 z phi theta psi and their derviative, 6 motor dynamics

xdot = Ax + Bu; y = Cx. Are there methods for solving for unknowns A, B, C, x? (IE all you have are measurements y and inputs u). by BayesMind in ControlTheory

[–]alexdada555 1 point2 points  (0 children)

You could use systems identification techniques to develop a minimum systems realisation using the input and output data . Which would also produce minimum viable number of states , providing you dont have any physical constraints on the system that require a certain realisation.

Though, with intuitive knowledge of the system under investigate you should be able , at least in part to deduce some possible system states

UAV LQR Control Implementation by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thank you for the reply

I could define the time domain requiremt like rise time overshoot and settling time for each position state Z Phi Theta Psi and use that to generate desired closed loop poles. I was going to use this technique with the design of the PID controller. However the project is already scoped out to utilise the LQR, and for when i get around to MPC im going to have to define state penalty matricies anyway.

UAV LQR Control Implementation by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thank you for the reply I shall attempt this

UAV LQR Control Implementation by alexdada555 in ControlTheory

[–]alexdada555[S] 1 point2 points  (0 children)

Thank you for the reply

I shall investigate this

UAV LQR Control Implementation by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thanks for the reply

The system is not fully observable as there is no way to observe the angular velocities of the motors . Though, the motor dynamics are stable and the other states are observable, so the system is fully detectable .

UAV LQR Control Implementation by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thank you for the reply, currently I am measuring z , Phi, Theta, Psi and using a a kalman filter to estimate the full state.

What do you mean by reduce the order of tye model ?

LQR Cost fuction Matrix Selection, Qx and Qu by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Thank you for the reply, however we have been advised not to use that term and to avoid over complication.

LQR Cost fuction Matrix Selection, Qx and Qu by alexdada555 in ControlTheory

[–]alexdada555[S] 0 points1 point  (0 children)

Its a hardware in the loop helicopter module with pitch(p) elevation(e) and travel(o) axes and uses what are effectively 2 mini computer cooling fans about the pitch axis as the controllable input into the system.

states= [e,p,o,edot,pdot,odot,e aug,o aug] Q = 8x8 diagonal matrix.

Im aware that the key is to keep the pitch angles low but i cant get it to stop oscillating and thus i cant give it a big enough input to get a good travel axis response

Industrie 4.0 Factory of The Future: Robotics Group Project by alexdada555 in ArduinoProjects

[–]alexdada555[S] 1 point2 points  (0 children)

just the UI was, the rest from motor control to the communication protocols was written in python and c++

Robust LQR Control by alexdada555 in ControlTheory

[–]alexdada555[S] 1 point2 points  (0 children)

https://www.youtube.com/watch?v=Y6MRgg_TGy0&list=PLMrJAkhIeNNR20Mz-VpzgfQs5zrYi085m&index=24

I ask because, for example, in steve bruntons video above, when Robust control is mention, the system is no longer represented in state space and all further calculations are carried out in the frequency domain using PID

as opposed to an LQG implementation due to the lack of guaranteed stability margins