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#Variables Controladas
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Reel di Tendenza
(12)
22.6K
CIDivergencia y Rotacional
#Matemáticas #campo #vectorial #divergencia #rotacional
🎞️ Shampoo Ahmed
@ciencias.tv
9.8K
EV¿Quieres sufrir? Llena tu código de Variables Globales💀
Al principio parecen fáciles: “accedo al dato desde donde sea”. ¡ERROR! 🚨
En realidad estás creando Spaghetti Code. Si cambias el valor en una función, rompes otra que ni sabías que existía a 500 líneas de distancia. Es la receta perfecta para bugs imposibles de rastrear.
#programacion #developer #software #ingenieria #tecnologia #estudiante #aprende #informatica #computacion #variables #javascript #python #code
@eve.devs
411
ROMedidas certeras se deben tomar para mantener estas variables controladas.
@rodolfomedinadelrio
2.1K
INLas variables de proceso son cantidades o condiciones físicas que afectan a los procesos industriales, estas necesitan ser monitoreadas y controladas para que los productos salgan con determinados estándaes de calidad.👍
Las variables más comúnes son presión, temperarura, flujo y nivel, 🦾 aunque hay otras, estás siempre están presentes en todos los procesos.😎
Hay diferentes puntos a tener en cuenta cuando trabajas con estas variables, aunque no son todas, en este video te cuento algunas para que las tengas presentes.👌
Comenta 👇¿qué otras consideracuones recomiendas tu?
#instrumentacion #instrumentaciónindustrial #controldeprocesos #ingenieria #instrumentacionycontrol
@instrumentation_to_go
326.1K
VASabes utilizar funciones de variable Real, te ayuda a resolver problemas.
#Matemáticas #matematica #funcion
@variable.real
53.4K
YANueva semana, nueva serie #software #programacion #ingenieria #codigo #variables
@yasminacodes
794.3K
ELLet’s solve this control systems exercise together: find the steady-state value of the step response of the system illustrated in the block diagram.
Comprising the closed-loop system architecture are the following fundamental components that allow for self-correction:
* The Controller (G_c): The “brain” that processes the signal.
* The Process or Plant (G): The physical system we are trying to influence.
* The Output Transducer (H): Often a sensor that measures the output and feeds it back to the start.
🔄 The Power of Feedback
Without feedback, a system is “blind” to external disturbances. Feedback allows us to compare where we are (Output) with where we want to be (Reference Input). If there is any difference between the two, the system drives the plant, via the actuating signal, to make a correction.
In this specific problem, our output transducer, or sensor, has unity gain, which means that H(s)=1. This is a special case where the actuating signal is precisely the error signal as it is the actual difference between the input and output.
⏱️ Efficiency via the Final Value Theorem
One of the most elegant tools in a control engineer’s toolkit is the Final Value Theorem (FVT). Usually, finding the steady-state behavior of a system would require us to perform an Inverse Laplace Transform to get back into the time domain, y(t), and then calculate the limit as t approached infinity.
FVT lets us skip the heavy lifting. By analyzing the behavior as s tends to 0 in the frequency domain, we can predict the system’s long-term “resting point” without ever leaving the s-plane.
#electrical #electricalengineering #controlsystem #electronics
@electricalmath
153.6K
EQThe Secret to Understanding Correlation Coefficients #statistics #math #datascience #correlation #Manim Master the Pearson Correlation Coefficient in seconds! This video breaks down the complex world of statistics by visualizing how 'r' values change across different scatter plots. From strong positive correlations (+0.95) to strong negative correlations (-0.95), you will see exactly how data points align with the line of best fit.
@equationsinmotion
265.7K
IL🚫 p-hacking 🚫
#statistics #science #estadística #investigation #math
@illariy.ai
1.0M
ENInverted Pendulum Control with PD, LQR & MPC in MATLAB
How do engineers stabilize an unstable system?
This project demonstrates the classic inverted pendulum on a cart, controlled using multiple control strategies including PD, LQR, and Model Predictive Control (MPC).
The simulation shows how the pendulum can be swung up from the downward position using an energy-based swing-up controller, and then stabilized near the upright equilibrium using optimal control techniques.
Built entirely in MATLAB, the project combines nonlinear dynamics, state-space modeling, and advanced control algorithms to visualize how unstable systems can be stabilized in real time.
⚙️ Project Highlights:
✅ Nonlinear dynamic modeling of the cart–pole system
✅ Energy-based swing-up control for the LQR controller
✅ PD controller for basic stabilization
✅ LQR optimal control for precise balancing
✅ Model Predictive Control (MPC) implementation
✅ Realistic MATLAB animation of cart-pole motion
✅ Automatic simulation plots for system performance
From instability to balance, this simulation demonstrates how modern control algorithms stabilize systems used in robotics, aerospace, and autonomous technologies.
📊 Perfect for:
• Control Systems students
• Robotics & Automation engineers
• MATLAB learners
• Mechatronics researchers
• Engineering final year projects
💡 A system that becomes unstable in seconds… can be stabilized with the right control strategy.
🔥 Save this reel if you enjoy robotics and control system simulations!
👇 Comment “Inverted Pendulum” if you want the MATLAB project files and report.
#MATLAB #InvertedPendulum #ControlSystems #LQRControl #MPCControl #RoboticsEngineering #Automation #EngineeringSimulation #EngineeringStudent #Mechatronics #ControlEngineering #EngineeringReels #TechReels #STEM #MechanicalEngineering
@engrprogrammer2494
338
MLMachine Learning me model train kar diya…
aur ek test par achha score bhi aa gaya.
Lekin problem ye hai ki shayad wo sirf usi data ko yaad karke baitha ho.
Isi liye ML engineers use karte hain Cross-Validation.
Isme dataset ko multiple parts me divide karke
model ko baar-baar train aur test kiya jata hai.
Simple language me:
Model ko ek nahi, multiple exams dene padte hain.
Tab pata chalta hai ki model actually smart hai ya sirf ratta maar raha hai.
#machinelearning
#crossvalidation
#datascience
#aiexplained
#concepts
#learnai
#techreels
#codingcommunity
#hindisong❤️
#programmerlife
@mlsimplifiedbyyash
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