Fundamentals of Control Systems Engineering Using MATLAB
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Welcome to the Course!
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Module 1: Fundamentals and Modeling of Linear Control Systems Using MATLAB
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Module 2: LTI System Modeling and Analysis Using MATLAB
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Module 3A: Fundamentals of Frequency Response & System RepresentationsTopic 1: Frequency Response Analysis – Bode Plot, Nyquist Diagram, & Gain–Phase Margins15m 2sTopic 2: MATLAB LTI Viewer – GUI-Based Response Analysis & Visualization14m 40sTopic 3: Effect of Poles, Zeros & System Order Using LTI Viewer15m 8sTopic 4: Time & Frequency Domain Representation of Continuous Systems (MATLAB)12m 39s
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Module 3B: Laplace and Frequency Domain Analysis of Control SystemsTopic 1: Laplace-Domain Analysis – Inverse Laplace & Partial Fraction Expansion16m 55sTopic 2: Frequency Function Analysis of LTI Systems Using MATLAB15m 3sTopic 3: Bode Plot Analysis in MATLAB – Scaling, Frequency Range & Visualization15m 16sTopic 4: Nyquist Plot Interpretation & Block Diagram Algebra21m 5s
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Module 4: Dynamic Response Analysis of Control SystemsTopic 1: Elements of Linear Control Systems – P, I & First-Order Lag15m 36sTopic 2: 1st, 2nd & Higher-Order Lag Systems – Step, Bode & Nyquist Analysis14m 51sTopic 3: Second-Order Oscillatory Systems – Damping Ratio, Natural Frequency, & Time Response14m 22sTopic 4: Effect of Damping Ratio on Second-Order Response & Stability15m 22sTopic 5: Effect of Zeros & Dead Time on Time & Frequency Response13mTopic 6: Modeling & Analysis of Dead-Time Systems Using Padé Approximation (MATLAB)17m 24s
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Module 5: Feedback Control Systems – Performance & Robustness AnalysisTopic 1: Negative Feedback – Stability, Robustness & Performance13m 49sTopic 2: Performance Analysis of Feedback Systems Using MATLAB16m 26sTopic 3: Characteristics of Negative Feedback – Performance Improvement & Linearization14m 51sTopic 4: Reference Tracking & Disturbance Rejection in Feedback Systems15m 39sTopic 5: Static Response – System Type, Integrators & Steady-State Error14m 6sTopic 6: Frequency-Domain Relationship Between Open-Loop & Closed-Loop Systems18m 44sTopic 7: Relationship Between Step Response Overshoot & Frequency-Domain Amplification9m 29s
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Module 6: Classical Stability Analysis of Control Systems (s-Domain Methods)Topic 1: Stability of Linear Control Systems – Definitions, BIBO Stability, & Pole Locations9m 58sTopic 2: Closed-Loop Stability Analysis Using Step Response, & Pole–Zero Maps9m 24sTopic 3: Stability Analysis Using Routh–Hurwitz Criterion11m 2sTopic 4: Stability Range of Loop Gain Using Routh–Hurwitz Criterion10m 21sTopic 5: Root Locus Analysis of Feedback Systems – Stability Boundaries & Gain Selection10m 52sTopic 6: Effect of Poles & Zeros on Root Locus and Closed-Loop Stability8m 37sTopic 7: Stabilization of Right-Half-Plane Pole Systems Using Root Locus9m 22s
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Module 7: Frequency-Domain Stability and Robustness AnalysisTopic 1: Nyquist Stability Criterion – Fundamentals and Closed-Loop Stability Conditions12m 57sTopic 2: Closed-Loop Stability Using Simplified Nyquist Criterion (MATLAB)6m 28sTopic 3: Nyquist Stability Analysis of Systems with Open-Loop Unstable Poles15m 48sTopic 4: Gain Margin and Phase Margin Computation Using MATLAB13mTopic 5: Frequency-Domain Stability Margins – Gain, Phase, & Delay Margin (MATLAB)15m 13sTopic 6: Frequency-Domain Robust Stability Analysis Using Modulus Margin & Sensitivity13m 44sTopic 7: Internal Stability Analysis Using Transfer Function Matrix10m 46s
The “Fundamentals of Control Systems Engineering Using MATLAB” course introduces the fundamentals of control systems engineering with a focus on modeling, analysis, and stability using MATLAB. It covers linear time-invariant (LTI) systems, time and frequency-domain response, and feedback system behavior.
Learners will study system representation using transfer functions and state-space models, along with the effect of poles and zeros on system response. Classical stability methods such as Routh–Hurwitz, Root Locus, and basic Nyquist concepts are also introduced.
MATLAB is used as a tool for modeling, simulation, and visualization of control systems, which are widely applied in industries such as robotics, automotive systems, aerospace, and industrial automation, where system modeling and stability analysis are essential for ensuring reliable performance.
By the end of the course, learners will be able to model basic control systems, analyze system behavior, and understand fundamental stability concepts using standard engineering tools.
What's included
- 7 Modules.
- 42 Lectures.
- 9.6 hours of Video Content.
- Certification of Completion.
