Park and inverse Park transformations convert between stationary and rotating reference frames.
https://zurl.co/Iqg2D
https://zurl.co/jNqEQ
#ParkTransformation #InverseParkTransformation #VectorControl #ElectricalEngineering #PowerSystems #ControlTheory #RenewableEnergy
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#controltheory
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2025 is looking like a great year for work at the intersection of #categorytheory, #systemstheory, #controltheory, #machinelearning and #probabilitytheory, this thread will be a very biased collection of works (in no specific order) I'm hoping to read as soon as possible!
Starting with:
"Logical Aspects of Virtual Double Categories"
https://mastoxiv.page/@arXiv_mathCT_bot/113921693949589956
mastoxivarXiv math.CT bot (@arXiv_mathCT_bot@mastoxiv.page)Logical Aspects of Virtual Double Categories
Hayato Nasu
https://arxiv.org/abs/2501.17869 https://arxiv.org/pdf/2501.17869 https://arxiv.org/html/2501.17869
arXiv:2501.17869v1 Announce Type: new
Abstract: This thesis deals with two main topics: virtual double categories as semantics environments for predicate logic, and a syntactic presentation of virtual double categories as a type theory. One significant principle of categorical logic is bringing together the semantics and the syntax of logical systems in a common categorical framework. This thesis is intended to propose a double-categorical method for categorical logic in line with this principle. On the semantic side, we investigate virtual double categories as a model of predicate logic and illustrate that this framework subsumes the existing frameworks properly. On the syntactic side, we develop a type theory called FVDblTT that is designed as an internal language for virtual double categories.
Taming the Wobble: An Arduino Self-Balancing Bot https://hackaday.com/2025/03/09/taming-the-wobble-an-arduino-self-balancing-bot/ #controltheory #selfbalancing #ArduinoHacks #RobotsHacks #Science #arduino #balance #robot
Hackaday · Taming The Wobble: An Arduino Self-Balancing BotGetting a robot to stand on two wheels without tipping over involves a challenging dance with the laws of physics. Self-balancing robots are a great way to get into control systems, sensor fusion, …
Taming the Wobble: An Arduino Self-Balancing Bot - Getting a robot to stand on two wheels without tipping over involves a challenging... - https://hackaday.com/2025/03/09/taming-the-wobble-an-arduino-self-balancing-bot/ #controltheory #selfbalancing #arduinohacks #robotshacks #science #arduino #balance #robot
Hackaday · Taming The Wobble: An Arduino Self-Balancing BotGetting a robot to stand on two wheels without tipping over involves a challenging dance with the laws of physics. Self-balancing robots are a great way to get into control systems, sensor fusion, …
Continued thread
Simulation here it is, control theory is still hard :( Anyone knowledgeable about #controltheory and interested in helping me out with this? Basically i get a sampled signal of relative increments and need to map them to a nice acceleration curve.
Boosts appreciated :)
Continued thread
You could think of a tach signal as a pulse density modulation. Each clock period is an implicit sample. If the tach is ticking at 1/200,000 the clock speed, then for 200,000 consecutive clocks, there are 0 samples, then there's a single 1 sample.
So I can run that through a low pass filter and get a very low amplitude speed signal? Are there feasible digital filters that work when the cutoff frequency is orders of magnitude below the sample rate?
DSP and control theory tooters, how do you smooth a tach signal?
I'm measuring a sequence of tachometer pulses, and I want to turn that into a smoothed current speed number. Everything I know about DSP uses a fixed sampling interval, but these aren't fixed -- the interval is the signal.
This has to be a well known problem with well known solutions...
Thank you.
ModConFlex' first researchers started around August 2023. Our presently 13 #MSCA researchers are coming from fields of #engineering, #physics and/or #mathematics. They are hosted by eight different #universities for their PhD and meet at least once a year at our annual network and training events.
Their research focuses on a range of topics from #ArtificialIntelligence over #ControlTheory (applied to floating #WindTurbines or, more theoretical, port Hamiltonian systems) to #FlexibleAircraft.
Last 2024 publication within the #ModConFlex project:
"LQR control for a system describing the interaction between a floating solid and the surrounding fluid" on #mathematics of #solid moving on the #sea and #control acting on the solid.
Co-authored by #ModConFlex #MSCA researcher Zhuo Xu and published in Mathematical Control and Related Fields:
https://www.aimsciences.org//article/doi/10.3934/mcrf.2024039
Congratulations to Zhuo for his first #publication !
Looking for this kind of confidence in a paper #systemstheory #cybernetics #controltheory
Tuning a PID controller can be quite tricky. In my new video, I demonstrate such tuning using #Python (so that you can see the graphs) for an inverted pendulum. Check it out!
https://youtu.be/hRnofMxEf3Q
If you are just starting in #ControlTheory or need a refresher, check out my introduction to #PIDController video! I cover the basic theory and how they work.
I know I haven't been posting much lately. I've just been slightly depressed about my job and stuff.
I've been working on making changes to improve things, but for now I feel like I'm in Limbo and I don't have a lot of motivation to be chatty and whimsical.
I'll be fine, though. I've been really enjoying my studies lately. Stepping through #ControlTheory exercises has given me an appreciation for #ElectricalEngineering that I never had before. 
I've been disappointed with the quality of resources I've found online for refreshing and expanding my #ControlTheory skills.
One big thing that I've been missing is example problems covering, say, #LyapunovStability and #TimeDelaySystems.
Thankfully, I've got the spouse's permission to use our joint account for purchasing textbooks.
But, does anybody have any recommendations for online resources or textbooks that cover these topics and have problems with solutions?
A review on different applications of control ideas to neuroscience, #motorcontrol and #decisionmaking, using in particular #controltheory and #perceptual #control.
The description of perceptual control seems suspiciously close to Friston's #activeinference...
A review on the #senseofagency, which in general is != #agency, but does share some commonalities, both ideological and methodological ones, see for example "theories of the sense of agency" where the #comparatormodel is none other than a portion of a #feedback #loop from #controltheory (the diagrams in this paper are admittedly quite weird though).
"Langevin algorithms for Markovian Neural Networks and Deep Stochastic control"
https://arxiv.org/abs/2212.12018
arXiv.orgLangevin algorithms for Markovian Neural Networks and Deep Stochastic controlStochastic Gradient Descent Langevin Dynamics (SGLD) algorithms, which add
noise to the classic gradient descent, are known to improve the training of
neural networks in some cases where the neural network is very deep. In this
paper we study the possibilities of training acceleration for the numerical
resolution of stochastic control problems through gradient descent, where the
control is parametrized by a neural network. If the control is applied at many
discretization times then solving the stochastic control problem reduces to
minimizing the loss of a very deep neural network. We numerically show that
Langevin algorithms improve the training on various stochastic control problems
like hedging and resource management, and for different choices of gradient
descent methods.
"Intrinsic Motivation in Dynamical Control Systems"
https://arxiv.org/abs/2301.00005
#DynamicalSystems
#ControlTheory #MachineLearning #ArtificialIntelligence
arXiv.orgIntrinsic Motivation in Dynamical Control SystemsBiological systems often choose actions without an explicit reward signal, a
phenomenon known as intrinsic motivation. The computational principles
underlying this behavior remain poorly understood. In this study, we
investigate an information-theoretic approach to intrinsic motivation, based on
maximizing an agent's empowerment (the mutual information between its past
actions and future states). We show that this approach generalizes previous
attempts to formalize intrinsic motivation, and we provide a computationally
efficient algorithm for computing the necessary quantities. We test our
approach on several benchmark control problems, and we explain its success in
guiding intrinsically motivated behaviors by relating our information-theoretic
control function to fundamental properties of the dynamical system representing
the combined agent-environment system. This opens the door for designing
practical artificial, intrinsically motivated controllers and for linking
animal behaviors to their dynamical properties.
Dynamic Programming is one way to arrive at the solution of the Markov Decision Process or MDP used in Reinforcement Learning (RL) problems.
In the third article on the Foundational RL series, I discuss dynamic programming and briefly talk about Approximate Dynamic Programming.
https://towardsdatascience.com/foundational-rl-dynamic-programming-28f96f6fb40e
Towards Data ScienceFoundational RL: Dynamic Programming - Towards Data Science
Time for a very late #introduction!
I'm an Associate Professor at #Arizona State University (#ASU), where I do a lot of inter- and multi-disciplinary work straddling animal behavior/behavioral ecology, autonomous systems/robotics, optimization/analytics, and machine learning/AI. Lately, I've been doing a lot of work with #ants, #bees, #swarmIntelligence, and #brain-inspired #AI. But my background is in #controlTheory.
Otherwise, yay to #dogs, #hiking, #nature, and #homeImprovement! 