Ultimate Automatic Control Theory in Electrical Engineering

Ultimate Automatic Control Theory in Electrical Engineering udemy course

Learn about automatic control including root-locus, PID, compensators, bode plot, and Nyquist for electrical engineering

Welcome to our course, "Ultimate Automatic Control Theory in Electrical Engineering," where you will learn everything about automatic control theory from scratch for electrical engineers.

What Students Will Learn from the Course:

• Fundamentals of Control Systems:

  • Understand the basic principles of automatic control.

  • Learn the importance and applications of control systems in various fields.

• Mathematical Modelling:

  • Develop mathematical models of electrical and mechanical systems.

  • Gain proficiency in Fourier Series, Fourier Transform, Laplace Transform, and Linear Time-Invariant (LTI) systems.

• Block Diagram and Signal Flow Graph Techniques:

  • Master the concepts of block diagrams and their reduction techniques.

  • Convert block diagrams into Signal Flow Graphs (SFG) and use Mason’s Formula.

• Time Response Analysis:

  • Analyze the time response of first and second-order systems.

  • Understand key specifications like rise time, peak time, and settling time.

• Stability Analysis:

  • Determine system stability using the Routh-Hurwitz criterion.

  • Calculate steady-state errors for different inputs and systems.

• Root-Locus and Frequency Response Methods:

  • Learn to sketch root-locus plots and analyze their effect on system behavior.

  • Perform frequency response analysis using polar plots, Nyquist criteria, and Bode plots.

• Compensators and PID Controllers:

  • Design and implement various compensators in control systems.

  • Understand and tune PID controllers using methods like Ziegler-Nichols and Particle Swarm Optimization.

• Introduction and Fundamentals of Distributed Generators (DGs):

  • Understand the basic concepts, importance, and classifications of distributed generators.

  • Learn about various DG technologies, including hydrogen fuel cells, ultra-capacitors, and flywheel energy storage systems.

  • Explore the principles, operation, and control goals of SSGs.

  • Examine the relationship between active and reactive power in synchronous machines.

  • Understand scalar control, generation of switching signals, and hysteresis current control.

• Advanced Control Techniques for SSGs:

  • Master space vector representation of balanced three-phase systems.

  • Gain proficiency in Clarke and Park transformations, frame transformations, and power-invariant methods.

  • Implement vector control strategies, including open-loop and closed-loop control of SSGs.

  • Learn to estimate the phasor angle, integrate filters with lag phase shifts, and apply phase-locked loop (PLL) systems.

• Photovoltaic (PV) Systems and Maximum Power Point Tracking (MPPT):

  • Understand the fundamentals of grid-connected PV systems and MPPT techniques.

  • Analyze and implement the "Perturb and Observe" method for tracking maximum power.

  • Learn vector control of single-stage PV systems.

  • Develop simulation models for grid-connected PV systems in MATLAB/Simulink.

  • Design PV arrays, control loops, and the rest of the system for comprehensive simulations.

  • Test and validate system performance, including voltage control at the point of common coupling.

  • Understand the switching states of a two-level inverter and implement sinusoidal pulse width modulation (SPWM) for precise control.

  • Learn feedforward decoupling control principles, implement control loops in MATLAB, and calculate equivalent impedance.

    
    

This course provides a comprehensive understanding of control systems, from fundamental concepts to advanced techniques, ensuring students are well-prepared to apply these skills in real-world scenarios.