TODAYS TECH

Master ANSYS FEA & CFD from Scratch — Turn Theory into Real Engineering Skills!

Every engineering student and professional reaches a stage where textbooks are no longer enough. The real advantage comes from mastering industry-standard simulation tools used by leading engineering companies worldwide.

I'm excited to announce our Online ANSYS FEA & CFD Mastercourse, designed to help you gain practical, job-ready simulation skills through hands-on projects and real engineering case studies.

👩‍🏫 Course Instructor: Areeba Fatima
Mechanical Engineer with 3+ years of experience in engineering simulations, specializing in:

✅ ANSYS Workbench
✅ Finite Element Analysis (FEA)
✅ Computational Fluid Dynamics (CFD – Fluent)
✅ Advanced Meshing Techniques
✅ Convergence Studies
✅ Result Interpretation
✅ Real-World Engineering Applications

📅 Course Starts: Mid-August 2026

🎯 Perfect For:
• Mechanical Engineering Students
• Final Year Project (FYP) Students
• Fresh Graduates
• Engineers looking to upgrade their simulation skills

📌 Register Now:
forms.gle/tZgAzQJkr1DTjfpF8

Don't just learn ANSYS—learn how engineers solve real-world problems using simulation.

💬 Tag a friend who wants to learn ANSYS, FEA, or CFD, and save this post for later!

#ANSYS #FEA #CFD #Engineering #MechanicalEngineering #MechanicalDesign #EngineeringSimulation #ANSYSWorkbench #ANSYSFluent #FiniteElementAnalysis #ComputationalFluidDynamics #CAE #Simulation #ProductDesign #StressAnalysis #ThermalAnalysis #FluidSimulation #EngineeringStudents #MechanicalEngineer #STEM #EngineeringEducation #LearnANSYS #CareerGrowth #SkillDevelopment #FutureEngineer #EngineeringLife #TechEducation #Engineer #DesignEngineering #SimulationEngineer

1 day ago | [YT] | 16

TODAYS TECH

🚀New Course: 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗠𝗼𝗱𝗲𝗿𝗻 𝗖++ 𝗳𝗼𝗿 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 & 𝗥𝗢𝗦𝟮

A while back, I ran a 𝘱𝘰𝘭𝘭 asking if people would be interested in a course like this, and the response was way bigger than I expected. So I promised I'd make it happen. Here it is.

👉 If you've ever 𝗵𝗶𝘁 𝗮 𝘄𝗮𝗹𝗹 debugging a segfault in your nav stack, wrestled with smart pointers in a ROS2 node, or wondered why your controller runs fine solo but chokes under concurrency, this one's for you.

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I'm teaming up with Ali Pahlevani (Robotics & Software Engineer) to run a 𝗳𝘂𝗹𝗹𝘆 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻, 𝗽𝗿𝗼𝗷𝗲𝗰𝘁-𝗯𝗮𝘀𝗲𝗱 course built specifically for robotics engineers who want to actually master the C++ that powers real robotic systems, not just pass a syntax quiz.

𝗪𝗵𝗮𝘁 𝘄𝗲'𝗹𝗹 𝗰𝗼𝘃𝗲𝗿:
🟢 Build Tools & the STL Library
🟢 Classes, Objects & OOP
🟢 Pointers & References
🟢 Templates & Lambdas
🟢 Concurrency
🟢 Exception Handling

Every concept is tied back to how it actually shows up in 𝗥𝗢𝗦𝟮 𝗰𝗼𝗱𝗲𝗯𝗮𝘀𝗲𝘀: node design, real-time constraints, memory safety, and the kind of production-grade patterns you need when your code is driving hardware, not just passing tests.

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📅 𝟴 𝗦𝗲𝘀𝘀𝗶𝗼𝗻𝘀 / 𝟮-𝗠𝗼𝗻𝘁𝗵 𝗖𝗼𝘂𝗿𝘀𝗲
🎓 𝗘𝗻𝗱-𝗼𝗳-𝗖𝗼𝘂𝗿𝘀𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
🎯 𝟭𝟬% 𝗢𝗙𝗙 for early-bird sign-ups & previous workshop attendees

📝 𝗣𝗿𝗲-𝗿𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: docs.google.com/forms/d/e/1FAIpQLSdrBAzeAzVooOAn65…

Tag a robotics engineer who needs to level up their C++, or drop a comment if you want in.

👉 𝗦𝗲𝗮𝘁𝘀 will be limited to keep it hands-on.


#Robotics #ROS2 #Cpp #OnlineCourse #SLAM #Autonomy

1 week ago | [YT] | 39

TODAYS TECH

🤖 Autonomous Mobile Robot Navigation with Theta*, APF, Pure Pursuit, LIDAR & SLAM in MATLAB

Ever wondered how autonomous robots navigate complex environments, avoid obstacles, and build maps at the same time?

This MATLAB project demonstrates a complete autonomous navigation system by integrating advanced path planning, obstacle avoidance, motion control, LIDAR sensing, and SLAM mapping into a single simulation.

🚀 Features Included

✅ Theta* Path Planning
✅ Artificial Potential Field (APF) Obstacle Avoidance
✅ Pure Pursuit Path Tracking Controller
✅ Real-Time LIDAR Sensor Simulation
✅ Occupancy Grid SLAM Mapping
✅ Adaptive Speed & Motion Control
✅ Automatic Path Re-planning & Stall Recovery
✅ Realistic 4-Wheel Mobile Robot Animation
✅ Multi-Window MATLAB Visualization
✅ Automatic HD MP4 Video Recording
✅ Complete MATLAB Source Code

📊 Simulation Outputs

📍 Planned vs Actual Robot Trajectory
📍 Real-Time Navigation Animation
📍 Live LIDAR Visualization
📍 Occupancy Grid SLAM Map
📍 Heading Angle Analysis
📍 Speed Profile
📍 Distance-to-Goal Analysis
📍 HD Simulation Videos

🧠 Technologies Used

• MATLAB
• Theta* Algorithm
• Artificial Potential Field (APF)
• Pure Pursuit Controller
• LIDAR Simulation
• Occupancy Grid SLAM
• Autonomous Mobile Robotics

📂 Complete Project Package

✔ MATLAB Source Code
✔ Modular Functions
✔ Professional Documentation
✔ Ready-to-Run Simulation
✔ HD Video Recording

🔗 Project Available Here:
engrprogrammer-shop.fourthwall.com/products/advanc…

💬 If you're interested in Robotics, MATLAB, Autonomous Navigation, SLAM, LIDAR, Control Systems, or Mechatronics Engineering, don't forget to Like 👍, Comment 💬, and Subscribe 🔔 for more robotics projects and simulations!

#MATLAB #Robotics #MobileRobotics #AutonomousRobot #RobotNavigation #ThetaStar #PathPlanning #ObstacleAvoidance #ArtificialPotentialField #PurePursuit #LIDAR #SLAM #AutonomousNavigation #ControlSystems #Mechatronics #Automation #Engineering #ArtificialIntelligence #Research #Simulation #EngineeringProjects #STEM

2 weeks ago (edited) | [YT] | 35

TODAYS TECH

UGV Trajectory Tracking Using Adaptive Nonlinear Control in MATLAB

How do autonomous ground vehicles accurately follow complex paths while maintaining stability and smooth steering?

This project presents an Ackermann-steered Unmanned Ground Vehicle (UGV) designed and simulated in MATLAB for tracking multiple reference trajectories using an Adaptive Nonlinear Controller based on Input-Output Linearization.

The vehicle successfully follows:

✔ Straight-Line Trajectory
✔ Circular Trajectory
✔ Rectangular Trajectory

The project includes realistic vehicle kinematics, steering dynamics, adaptive gain control, STL-based 3D visualization, real-time animation, and performance analysis.

⚙️ Project Highlights:

✔ Adaptive Nonlinear Trajectory Tracking Controller
✔ Input-Output Linearization Control Strategy
✔ Ackermann Steering Vehicle Model
✔ Circular, Line & Rectangle Path Tracking
✔ Real-Time 3D STL-Based UGV Animation
✔ Tracking Error & Control Signal Analysis
✔ Publication-Quality MATLAB Plots
✔ Complete MATLAB Source Code

📊 Generated Outputs:

✔ Desired vs Actual Trajectory Comparison
✔ Position Tracking Error Analysis
✔ Linear Velocity Response
✔ Angular Velocity Response
✔ Steering Angle Response
✔ Adaptive Gain Evolution
✔ Professional Result Figures

🧠 Key Insight:

Traditional path-following approaches often struggle with nonlinear vehicle behavior and steering constraints. By combining Jacobian-based feedback linearization with adaptive gain scheduling, the UGV achieves smooth and accurate trajectory tracking across multiple path geometries.

💡 Result:
Accurate path tracking, smooth steering behavior, robust control performance, and realistic vehicle visualization in a complete MATLAB simulation framework.

📂 Complete Project Package Available:

✅ MATLAB Source Code
✅ STL-Based UGV Model
✅ Real-Time Animation
✅ Documentation
✅ Result Plots

🔗 Project Link:
engrprogrammer-shop.fourthwall.com/products/ugv-tr…

🔥 Repost if you're interested in Robotics, Autonomous Vehicles, MATLAB, and Control Systems.

#MATLAB #Robotics #UGV #AutonomousVehicle #ControlSystems #Mechatronics #TrajectoryTracking #PathTracking #AdaptiveControl #NonlinearControl #VehicleDynamics #Automation #EngineeringProjects #Research #Simulation #MobileRobotics #RobotNavigation #ControlEngineering #MATLABProgramming #FYP

1 month ago | [YT] | 44

TODAYS TECH

🤖 LQR vs PID Control for Self-Balancing Robot in Simulink (Simscape)

How do engineers stabilize an inherently unstable system in real time?

This project demonstrates a self-balancing robot (inverted pendulum system) modeled and simulated in MATLAB Simulink & Simscape, comparing two widely used control strategies:

PID Controller
Linear Quadratic Regulator (LQR)

The system includes full physical modeling, state-space control design, and real-time simulation, visualized through robot animation and time-domain response analysis.

⚙️ Project Highlights:

✔ Simulink + Simscape physical modeling of inverted pendulum robot
✔ Realistic multi-domain system simulation (mechanical + control)
✔ PID controller design and tuning
✔ LQR optimal state-feedback controller implementation
✔ System response analysis (angle, position, velocity, angular velocity)
✔ Stability and performance evaluation using RMSE and dynamic metrics
✔ MATLAB-based animation and visualization

📊 Key Results:

LQR Controller (Optimal Control)

Angle RMSE: 0.0076 rad
Position RMSE: 0.0038 m
Maximum Tilt: 1.29°
Highly stable and smooth response

PID Controller (Classical Control)

Angle RMSE: 0.199 rad
Position RMSE: 0.046 m
Maximum Tilt: 29.1°
Large oscillations and weak stability performance
🧠 Engineering Insight:

This simulation highlights a fundamental difference in control design:

PID control relies on error correction and struggles with highly unstable nonlinear systems
LQR uses state-space optimization to minimize both error and control effort simultaneously

For underactuated systems like inverted pendulum robots, LQR provides significantly superior stability and performance.

📦 Project Includes:

✔ Complete Simulink + Simscape model
✔ MATLAB simulation scripts
✔ LQR & PID controller implementation
✔ Full response plots and performance metrics
✔ Detailed technical report (PDF)
✔ Professional presentation (PPT)
✔ Ready-to-use academic/project documentation

🎯 Ideal For:

• Control Systems Engineering students
• Robotics & Mechatronics projects
• MATLAB/Simulink learners
• Final Year Project (FYP) submission
• Research & simulation-based studies

💡 A highly unstable system that falls within seconds… can be perfectly stabilized using optimal control design.

🔗Downlaod Complete Project with Report:

engrprogrammer-shop.fourthwall.com/products/self-b…

#MATLAB #Simulink #Simscape #ControlSystems #Robotics #LQR #PIDControl #SelfBalancingRobot #InvertedPendulum #Mechatronics #Automation #EngineeringSimulation #FinalYearProject #FYP #ControlEngineering #RoboticsEngineering #STEM

1 month ago | [YT] | 117

TODAYS TECH

Fuzzy Logic Obstacle Avoidance Robot Simulation in Simulink

From fuzzy rules to intelligent navigation ✨

This project demonstrates a fully simulated differential drive mobile robot capable of autonomously avoiding obstacles and navigating toward a target using a Mamdani Fuzzy Logic Controller in MATLAB & Simulink.

🎯 Features:
✔️ Fuzzy Logic Controller (FIS)
✔️ Differential Drive Robot Model
✔️ Intelligent Obstacle Avoidance
✔️ Goal-Seeking Navigation
✔️ Real-Time Simulink Simulation
✔️ Custom Membership Functions
✔️ Rule-Based Decision Making
✔️ Robot Animation & Visualization

📊 Concepts Covered:
• Robot Kinematics
• Fuzzy Inference Systems
• Mobile Robotics
• Autonomous Navigation
• Path Planning
• Intelligent Control Systems

⚙️ Built entirely in MATLAB & Simulink

This is where robotics, control systems, and artificial intelligence come together to transform sensor data into intelligent motion 🤖🚀

💡 Want the complete project files?
engrprogrammer-shop.fourthwall.com/products/fuzzy-…



🔥 Save this post for your robotics projects and share it with fellow engineers!

#robotics #fuzzylogic #matlab #simulink #obstacleavoidance #pathplanning #mobilerobotics #controlsystems #artificialintelligence #engineering #automation #roboticsengineering #engineeringstudent #matlabsimulation #autonomousrobot #autonomoussystems #mechatronics #fyp #finalyearproject #engineeringprojects #stem #ai #navigation #simulation #research #robotcontrol #intelligentcontrol #matlabcode #robotnavigation #roboticsproject

1 month ago | [YT] | 58

TODAYS TECH

🤖 SCARA Robot Trajectory Tracking using PID Control in MATLAB/Simulink & Simscape

➡ Complete simulation of SCARA robotic manipulator
➡ Physics-based modeling using Simscape Multibody
➡ Forward & Inverse Kinematics implementation
➡ PID-based closed-loop control for precise motion
➡ Smooth trajectory generation and tracking
➡ Real-time 3D visualization and animation
➡ Integration of CAD model (SolidWorks) with simulation
➡ Modular and well-structured model for learning and scalability

✨ Why this matters:
Trajectory tracking in SCARA robots is critical for high-speed industrial tasks such as pick-and-place and assembly operations. Achieving precise motion requires tight integration between kinematic modeling and control design.
This project demonstrates how classical PID control, when properly tuned, can ensure stable and accurate tracking despite nonlinearities in robotic motion. By combining kinematics, dynamics (via Simscape), and control, the system reflects real-world robotic applications used in modern automation industries.

📊 Key Highlights:
✔ Complete kinematic modeling (FK & IK) for SCARA manipulator
✔ PID-based trajectory tracking for stable and accurate motion
✔ Physics-based simulation using Simscape Multibody
✔ Real-time 3D visualization of robotic movement
✔ CAD-integrated robotic model (SolidWorks)
✔ Clean and reusable Simulink architecture
✔ Includes report and presentation for academic/professional use

💡 Future Potential:
This project can be extended to:
➡ Advanced control (LQR, MPC, Adaptive, AI-based control)
➡ Obstacle avoidance and intelligent path planning
➡ Vision-based pick-and-place systems
➡ Real-time hardware implementation (Arduino/ROS)
➡ Digital twin and smart manufacturing applications

🔗 Download Complete project Now:
engrprogrammer-shop.fourthwall.com/products/scara-…

🔁 Repost to support robotics innovation & engineering learning!

#Robotics #MATLAB #Simulink #Simscape #PIDControl #SCARA #RobotManipulators #ControlSystems #Automation #Mechatronics #EngineeringProjects #Simulation #STEM #EngineeringEducation

2 months ago | [YT] | 53

TODAYS TECH

🚁 Quadcopter Control Using LQR in MATLAB

➡ Nonlinear dynamic modeling of a quadcopter (6-DOF UAV system)
➡ State-space representation of translational and rotational dynamics
➡ Linearization around hover equilibrium for control design
➡ LQR optimal controller for position and attitude stabilization
➡ Full-state feedback control using gain matrix K
➡ 3D trajectory tracking with real-time simulation and visualization
➡ Stable flight performance for multiple reference paths (circle, helix, figure-8)

✨ Why this matters:
The quadcopter is a highly coupled, nonlinear, and inherently unstable system, meaning every motion in one axis affects others simultaneously.

To achieve stable flight, the controller must continuously compute optimal control inputs that balance tracking accuracy and control effort.

This project demonstrates how modern optimal control theory (LQR) can stabilize complex UAV dynamics efficiently compared to classical tuning-based methods.

It bridges the gap between:
➡ Nonlinear dynamics
➡ State-space modeling
➡ Optimal control design
➡ Real-time UAV behavior simulation

These concepts are widely used in autonomous drones, aerospace systems, robotics, and intelligent control applications.

📊 Key Highlights:
✔ Complete nonlinear quadcopter dynamics modeling
✔ State-space formulation (A, B matrices)
✔ LQR controller design using Riccati equation
✔ Optimal gain matrix computation (K)
✔ Smooth 3D trajectory tracking
✔ Real-time MATLAB animation and visualization
✔ Reference vs actual trajectory comparison

💡 Future Potential:
This framework can be extended toward:
➡ LQR vs PID vs MPC performance comparison
➡ Robust / adaptive LQR design under disturbances
➡ Wind disturbance and sensor noise modeling
➡ Reinforcement learning-based UAV control
➡ Real-time hardware implementation on drones
➡ ROS + Gazebo integration for robotics systems

🔗 For students, engineers & robotics enthusiasts:
This MATLAB simulation provides a practical foundation for understanding optimal control theory applied to real UAV systems, making it ideal for academic projects, research, and engineering portfolios.

🔁 Repost to support robotics research & engineering education!

📌Download Now: engrprogrammer-shop.fourthwall.com/products/quadco…

#Robotics #MATLAB #ControlSystems #UAV #Quadcopter #LQR #OptimalControl #AerospaceEngineering #EngineeringProjects #Simulation #StateSpace #DroneControl #Mechatronics #EngineeringEducation #DynamicSystems

2 months ago | [YT] | 103

TODAYS TECH

🚁 PID-Controlled Quadcopter Simulation

From equations to flight ✨
This project demonstrates a fully simulated quadcopter controlled using a cascaded PID controller for stable trajectory tracking in 3D space.

🎯 Features:
✔️ Nonlinear quadcopter dynamics
✔️ Cascaded PID (position + attitude control)
✔️ Smooth trajectory tracking
✔️ Real-time 3D animation
✔️ Auto-generated simulation video

📊 Trajectories tested:
• Circle
• Figure-8
• Helix
• Mission: Takeoff → Move → Land

⚙️ Built entirely in MATLAB

This is how control theory comes to life — turning math into motion 🚀

💡 Want the full code & project files?
engrprogrammer-shop.fourthwall.com/products/quadco…

#quadcopter #pidcontrol #controlsystems #matlab #robotics #uav #engineeringstudent #simulation #automation #mechatronics #roboticsengineering #fyp #stem #engineeringprojects

2 months ago | [YT] | 110

TODAYS TECH

I’ve been consistently creating engineering content for students and learners — tutorials, projects, and resources — all shared to help others grow.

A lot of time, effort, and energy goes into keeping this going and improving it further.

If my content has ever helped you in your journey, and you’d like to support it so I can continue creating more, you can do so here ☕

👉 buymeacoffee.com/engrprogrammer

Even small support helps me keep this work alive and growing.

Thank you to everyone who has been part of this journey ❤️

3 months ago (edited) | [YT] | 7