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QUPID CONTROLLA GIVE YOU GODLINE POWAHHHHH #viralreels #fyp #makersgonnamake #techreels #pid
@quantum_projects_yt
#Pid Control Algorithm
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GADemonstration of PID control using a differential drive vehicle I made! If you don’t know what PID is, it’s essentially a method to control error. In this case, the error can be defined as the difference between the actual angle of the car and the calculated angle required to reach the target point. The heading is constantly tracked through a magnetometer which returns the exact heading of the robot in degrees. The robot takes the error and adjusts the motor speed so that it faces the proper orientation. I’m also using 2 DC motors with encoders to track the position of the robot through odometry calculations. I’m planning on doing a more in depth video on PID control so stay tuned for that! #engineering #arduino #diy #science #senior
@galbitangg
10.9K
REThe PID algorithm determines the control action.
“P” stands for Proportional, “I” stands for Integral, and “D” stands for Derivative.
Adjusting these parameters changes how the controller responds.
To learn more read the full article from the lin in the bio🔗
#pidcontrollers #industrialautomation #controlsystems #automationengineering
@realparsdotcom
293.4K
EL🎛️ ¿Qué es un controlador PID? Una explicación simple… y muy poderosa
En este video se resume de forma clara cómo funciona el PID (Proporcional–Integral–Derivativo):
P: si no estás donde quieres estar, muévete hacia ahí.
I: si llevas mucho tiempo sin llegar, muévete más rápido.
D: si ya estás cerca, desacelera para no pasarte.
Los motores (y muchos sistemas reales) no arrancan ni se detienen instantáneamente. Por eso aparecen sobreimpulsos, errores en régimen permanente y oscilaciones. El PID permite ajustar estos tres efectos con parámetros bien definidos y lograr un comportamiento estable y preciso.
Una explicación sencilla que ayuda a entender por qué el PID sigue siendo uno de los algoritmos más usados en control automático.
📂 Puedes descargar los archivos del proyecto aquí:
👉 https://drive.google.com/file/d/0BzmbIyWePioHWVhHZE04QmVnck0/view?resourcekey=0-iivFjFSA6x_Rj1QQKSBgCQ
🎓 Conoce nuestros cursos completos de control en:
👉 https://sites.google.com/view/elingedecontrol/inicio
🎥 Crédito del video: Voltix Electronics Lab
(Gracias también a Warlax 56 por la explicación intuitiva del PID)
#PID #ControlAutomatico #IngenieriaDeControl #Motores #SistemasDinamicos #ControlIndustrial #EducacionEnIngenieria #ElIngeDeControl
@elingedecontrol
236.4K
SEThe 3-letter algorithm that keeps drones, thermostats, and self-driving cars perfectly on target. See PID in action! #engineering #PIDcontroller #controlsystems #robotics #learnengineering #science
@see.it.click
1.3K
BEWhat is PID Control?
PID (Proportional-Integral-Derivative) control is a widely used control strategy in electrical instrumentation and automation. It's a feedback control mechanism that helps regulate and stabilize processes by adjusting the output based on the error between the desired setpoint and the actual process value.
Origin and History
The concept of PID control dates back to the 19th century, but it gained popularity in the 1940s and 1950s in the process control industry, particularly in the chemical and oil refining sectors.
Definition of Each Term in PID
1. Proportional (P): The proportional term adjusts the output based on the current error value. It's proportional to the error, hence the name.
2. Integral (I): The integral term adjusts the output based on the accumulation of past error values over time. It helps eliminate steady-state errors.
3. Derivative (D): The derivative term adjusts the output based on the rate of change of the error value. It helps improve stability and responsiveness.
Applications of PID Control
PID control is widely used in various industries, including:
1. Process control (chemical, oil refining, power generation)
2. Temperature control (HVAC, refrigeration)
3. Motor control (speed, position)
4. Robotics
5. Aerospace
6. Automotive
How to Use PID Controls
To implement PID control:
1. Define the process and its dynamics
2. Set the desired setpoint
3. Choose the PID gains (Kp, Ki, Kd) through tuning methods (e.g., trial-and-error, Ziegler-Nichols)
4. Implement the PID algorithm in a controller or software
5. Monitor and adjust the PID gains as needed
Here's a simple yet effective video that illustrates how PID control works.
This video uses animations and graphs to demonstrate the basic principles of PID control, making it easy to understand for beginners.
@beinamr
118.0K
MATaming the mechanical beast! 🤖🎛️
Ever wonder how a drone hovers perfectly in place or how cruise control keeps your car at the exact right speed? It is all thanks to the magic of PID Control. But finding the perfect tuning? That is where the real engineering happens. 📉
Let's watch the graphs in real-time as we build a controller from scratch:
📈 1. Proportional (P) Only: This gives the system a strong kick toward our target (the set point). It is fast, but it overshoots and leaves an annoying gap called steady-state error.
⏳ 2. Adding Integral (PI): The 'I' looks at past mistakes and forces that gap to close completely. But notice the trade-off? The system gets wobbly and continues to oscillate!
🛑 3. Swapping to Derivative (PD): The 'D' acts like the brakes. It predicts the future to dampen those oscillations and smooth things out. But without our 'I' term, that annoying gap comes right back!
🎯 4. Full PID (Ziegler-Nichols Tuned): Instead of guessing the gains (Kp, Ki, Kd) for hours on end, engineers use the Ziegler-Nichols method. By pushing the system to its limit and using a set of specific formulas, we can mathematically calculate the perfect sweet spot.
The result? A fast, smooth response that locks perfectly onto the target with zero steady-state error. This is why visualizing the math makes all the difference! ✨
What is the most frustrating system or robot you have ever had to tune? Let’s hear your control lab horror stories in the comments! 👇
#PIDController #ControlSystems #Mechatronics #RoboticsEngineering #ElectricalEngineering
@mae.academy
624
CO(Part 2/2) In this video, I demonstrate the Thrust Vector Control (TVC) system powered by a PID-based control algorithm filtered through a Kalman Filter for enhanced stability and precision.
The system runs on the Vega FC-301 Flight Computer, developed by me under Cosmic Aerospace Technologies — a startup dedicated to creating high-end, affordable flight computers, avionics, and electronics for rocketry enthusiasts and engineers alike.
You can clearly see the stability, responsiveness, and precision of both the flight computer and gimbal throughout this demo.
🌐 Learn more at: cosmicaero.space
Tags:
#TVCSystem #PIDControl #KalmanFilter #FlightComputer #ModelRocketry
#arduino #tvc #pcb #eda #rocketry #space #rockets #engineering #electronics #electricalengineering
@cosmic_aerospace
191.5K
COLearning how to tune a PID for a drone. Any suggestions?
#drone #fpvdrone #raspberrypipico #engineering #flightcontroller
@codeontheedge
410.7K
MEA PID control loop uses Proportional, Integral, and Derivative terms to minimize error between a system’s setpoint and actual output. It’s the backbone of modern automation, used in motors, temperature control, and robotics.
#BrainNourishment #MechanicalStan #StanExplains #Engineering #ControlSystems #PIDController #Automation #Robotics #MechanicalEngineering #Mechatronics
@mechanical.stan
93.8K
SIHow to create the ULTIMATE PRD👇
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FOR ALL VIBECODERS:
The PRD is the most important part of building an app. It’s the ultimate source of truth and context for the AI to build out your app.
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A highly-detailed PRD might lead to a couple hours or days of development time…
A horrible PRD might lead you to a burn out and to never finish your product.
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PAY ATTENTION🚨 This video includes ALL the information your PRD should contain.
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•
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#ai #chatgpt #vibecoding #coding #entrepreneur
@sina.growthtech
149.3K
EN3-DOF Robotic Arm Kinematics & PID Trajectory Tracking in MATLAB
➡ User-selectable trajectories: Circle, Infinity (∞), Rectangle, Helix
➡ Analytical Inverse Kinematics with smooth configuration selection
➡ Forward Kinematics with real-time 3D visualization
➡ PID-based joint control for precision tracking
➡ Live end-effector path tracing & motion analysis
✨ Why this matters:
Understanding the relationship between joint angles and end-effector motion is fundamental in robotics. From automation and pick-and-place systems to advanced AI-driven manipulators, accurate kinematic modeling and PID control are the backbone of intelligent robotic systems.
This simulation not only visualizes robotic motion but also demonstrates real-time trajectory tracking, control stability, and smooth joint coordination, making it ideal for learning and research.
📊 Key Highlights:
PID-tuned joints for smooth, stable motion ✅
Correct DH parameters (α₁ = 90°, α₂ = 0°, α₃ = 0°)
Realistic 3D animation with color-coded links & joints
Trajectory generation with adjustable resolution
MP4 video export for presentations & documentation
💡 Future Potential:
This project can be extended to:
➡ Obstacle avoidance & path planning
➡ AI / optimization-based trajectory control
➡ ROS integration & hardware implementation
➡ Adaptive or intelligent control systems
🔗 For students, engineers & robotics enthusiasts:
This is a ready-to-run MATLAB project for mastering robot kinematics, PID control, and trajectory tracking in a practical way.
🔁 Repost to support robotics innovation! 🔁
#3DOFRobot #RobotArm #Robotics #RobotKinematics #ForwardKinematics #InverseKinematics #PIDControl #TrajectoryTracking #MATLAB #MATLABRobotics #Automation #Mechatronics #ControlSystems #EngineeringLife #STEM #RoboticsEngineering #3DSimulation #RobotSimulation #AIinRobotics #EngineeringProjects
@engrprogrammer2494
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#Pid Control Algorithm is one of the most engaging trends on Instagram right now. With over thousands of posts in this category, creators like @galbitangg, @mechanical.stan and @elingedecontrol are leading the way with their viral content. Browse these popular videos anonymously on Pictame.
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