❇️"Designing Fuzzy Systems with Recursive Least Squares | MATLAB Simulink Tutorial for Cruise Control and DC Motor Speed"❇️

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#FuzzyLogic #MATLABSimulink #ControlSystems #RecursiveLeastSquares #GaussianFunctions #SystemTesting #OptimalControl #AdaptiveControl #TechTutorial #Engineering #MATLABCoding #RealTimeControl #AlgorithmExplanation #VersatileSystems #OnlineLearning

❇️Transfer Function Coefficient Identification with MATLAB: Markov Series and Hankel Matrix Method

Description:

"Dive into MATLAB as we explore the Markov series and Hankel matrix method for identifying transfer function coefficients. This tutorial guides you through the step-by-step process of extracting numerator and denominator coefficients, shedding light on the intricacies of system identification. Perfect for engineers and enthusiasts looking to enhance their understanding of transfer function modeling.
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#MATLAB #TransferFunction #SystemIdentification #ControlSystems #Engineering #MarkovSeries #HankelMatrix #MATLABCoding #CoefficientIdentification

❇️پروژه درس شناسایی سیستم

—شناسایی سیستم به صورت فضای حالت
—شناسایی سیستم با مدل های ARX , OE , BJ
—شناسایی غیر خطی NLARX ,...
—شناسایی جعبه خاکستری
—بهبود مدل با استفاده از همرشناین وینر
—شناسایی حوزه زمان سیستم با تولباکس شناسایی سیسیتم
—طراحی کنترل کننده پیش بین برای مدل شناسایی شده
—مقایسه کنترل کننده پیش بین با کنترل کننده PID همراه با نویز در خروجی و ورودی سیستم و ردیابی ورودی مرجع
—راهکاری ساده برای فیلتر نویز و...
دانلود:
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🔰Linear Control Training Workshop - Session 1

🟢This video covers the first session of a comprehensive linear control training workshop. Linear control theory is fundamental to understanding and designing control systems in various engineering applications.

In this session, you'll learn the basics of linear control, including:
🔹 Introduction to control systems and their components
🔸 Modeling linear systems using transfer functions and state-space representations
🔹Analyzing system stability and performance using tools like root locus and frequency response methods
🔸Basic control design techniques like PID control
Whether you're a student, engineer, or professional in the field of control systems, this video will provide a solid foundation for understanding linear control concepts and techniques.
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#LinearControl #ControlSystems #ControlTheory #SystemModeling #SystemStability #ControlDesign #EngineeringEducation

🔰Linear Control Training Workshop - Session 2

🔹Partial Fraction Expansion: Learn how to use the residue() command to easily perform partial fraction expansion on transfer functions. See examples of expanding proper and improper rational functions.
🔸Transforming Mathematical Models: Discover how to convert between different representations of dynamic systems using commands like tf2ss, ss2tf, zp2tf, etc. Examples show conversions between transfer functions, state-space models, pole-zero form, and discrete-time systems.
🔹Block Diagram Modeling: Master the techniques for representing interconnected systems with transfer function or state-space blocks. Learn the MATLAB syntax for series, parallel, and feedback connections. See how to extract the overall transfer function or state-space model.
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#MATLAB #ControlSystems #DynamicSystems #TransferFunctions #StateSpace #BlockDiagrams #ModelConversion #PartialFractions #MATLABTutorial #ModelingAndAnalysis

🔰Linear Control Training Workshop - Session 3

🔵Learn how to analyze the transient response of control systems using MATLAB in this comprehensive tutorial video. We cover step response, impulse response, ramp response, and response to arbitrary inputs. Discover how to obtain key parameters like rise time, peak time, maximum overshoot, and settling time. We also explore generating 3D plots of response curves. Improve your understanding of control system behavior and master transient response analysis with MATLAB.
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#MATLAB #ControlSystems #TransientResponse #StepResponse #ImpulseResponse #RampResponse #RiseTime #PeakTime #Overshoot #SettlingTime #3DPlots #EngineeringTutorial #ControlTheory

🔰Linear Control Training Workshop - Session 4

🔵In this MATLAB tutorial video, we dive into the powerful control systems analysis and design capabilities of MATLAB. Learn how to create and interpret root locus plots to analyze system stability and transient response characteristics. We then explore various control system compensation techniques, including lead, lag, and lag-lead compensation, and how to design compensators using the root locus approach.

🔸Generating root locus plots with MATLAB
🔹Effects of poles and zeros on root locus shape
🔸Finding gain values at points on the root locus
🔹Plotting root loci with damping ratio and natural frequency lines
🔸Lead compensator design
🔹Lag compensator design
🔸Lag-lead compensator design
🔹Analyzing compensated vs. uncompensated system responses
🔸Parallel compensation and velocity feedback
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#MATLAB #ControlSystems #RootLocus #SystemStability #LeadCompensation #LagCompensation #LagLeadCompensation #ControlSystemDesign

✳️Deep Belief Network Controller: A Modern Alternative to PID in Simulink

🔰Discover how to replace traditional PID controllers with advanced Deep Belief Network (DBN) controllers in Simulink. This tutorial demonstrates the step-by-step process of implementing a DBN controller, showcasing its advantages over PID in complex control systems. Learn how this cutting-edge AI technique can enhance system performance and adaptability across various engineering applications. Whether you're a control systems engineer, an AI enthusiast, or a student exploring advanced control methods, this video offers valuable insights into the future of intelligent control systems."
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#DeepBeliefNetwork #ControlSystems #Simulink #MachineLearning #PIDController #AIControl #EngineeringTutorial #AdvancedControl #MATLAB #IntelligentSystems

✳️Inverted Pendulum Control: RL + MPC Implementation

1️⃣ Reinforcement Learning Features:
- Q-Learning for system identification
- Self-learning pendulum balancing
- No prior model needed

2️⃣ MPC Implementation:
- Real-time optimization
- Constraint handling
- Precise position/angle control

3️⃣ Hardware:
- DC motor (50:1 gearbox)
- Dual encoders
- STM32 controller
- Custom PWM driver

4️⃣ Performance:
- Upright stabilization
- Disturbance rejection
- Accurate tracking

By: Javad Safaei
Supervisor: Naser Pakar
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#InvertedPendulum #ReinforcementLearning #ModelPredictiveControl #Robotics #ControlSystems #Engineering