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Advanced Linear Continuous Control Systems

Engineering Academy

Engineering Academy

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Preview this course

Advanced Linear Continuous Control Systems

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    Engineering Academy

    Engineering Academy

    Learn Without Limits: Free Engineering Courses

  • Course type

    Watch to learn anytime

  • Course duration

    848 Min

  • Course start date & time

    Access anytime

  • Language

    English

Why enroll

Participants should join this course to build a strong foundation in advanced control systems using clear and practical explanations. It helps learners understand state-space modeling, stability, and controller design with real examples and MATLAB practice. The course is useful for both academic learning and real-world engineering applications.

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Course content

The course is readily available, allowing learners to start and complete it at their own pace.

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Advanced Linear Continuous Control Systems

30 Lectures

848 min

  • Lesson icon

    Advanced Linear Continuous Control Systems

    Preview icon

    Preview

    2 min

  • Lesson icon

    Introduction to State Space

    23 min

  • Lesson icon

    State Space Representation

    26 min

  • Lesson icon

    State Space Representation: Companion Form (Controllable Canonical Form)

    22 min

  • Lesson icon

    State Space Representation: Extended Controllable Canonical Form

    29 min

  • Lesson icon

    State Space Representation: Observable Canonical Form

    26 min

  • Lesson icon

    State Space Representation: Diagonal Canonical Form (Part-I)

    23 min

  • Lesson icon

    State Space Representation: Diagonal Canonical Form (Part-II)

    22 min

  • Lesson icon

    State Space Representation: Jordan Canonical Form

    29 min

  • Lesson icon

    State Space Representation: Numerical Examples on State space Modelling (Part-I)

    28 min

  • Lesson icon

    State Space Representation: Numerical Examples on State space Modelling (Part-II)

    38 min

  • Lesson icon

    Modelling of Mechanical Systems in State Space

    34 min

  • Lesson icon

    Modelling of DC Servo Motor (Part-I)

    39 min

  • Lesson icon

    Modelling of DC Servo Motor (Part-II)

    20 min

  • Lesson icon

    Determination of Transfer Function from State Space Model (Part-II)

    15 min

  • Lesson icon

    Determination of Transfer Function from State Space Model (Part-I)

    45 min

  • Lesson icon

    Stability Analysis in State Space (Part-II)

    21 min

  • Lesson icon

    Stability Analysis in State Space: Concept of Eigenvalues and Eigenvectors (Part-I)

    34 min

  • Lesson icon

    Stability Analysis in State Space: Lyapunov Stability Analysis (Direct Method) Part-V

    28 min

  • Lesson icon

    Stability Analysis in State Space: Lyapunov Stability Analysis (Stability Criterion) Part-IV

    27 min

  • Lesson icon

    Stability Analysis in State Space: Lyapunov Stability Analysis (Sylvester’s Criterion) Part-III

    36 min

  • Lesson icon

    Concept of Diagonalization

    24 min

  • Lesson icon

    Solution of State Equation

    25 min

  • Lesson icon

    Solution of State Equation (Forced System)

    34 min

  • Lesson icon

    State Transition Matrix (Part-I)

    32 min

  • Lesson icon

    Steady State Error for State Space System

    32 min

  • Lesson icon

    State Transition Matrix (Part-II)

    25 min

  • Lesson icon

    State Transition Matrix using Cayley-Hamilton Theorem (Part-III)

    41 min

  • Lesson icon

    Controllability in State Space (Part-I)

    29 min

  • Lesson icon

    MATLAB Programming with State Space

    39 min

Course details

This course is designed to help learners clearly understand the principles and applications of advanced control engineering, which plays a vital role in many engineering fields such as electrical, mechanical, aerospace, robotics, and automation. As modern engineering systems become more complex and interconnected, a strong foundation in advanced control concepts is essential.The course mainly focuses on linear continuous-time control systems and builds a solid understanding of their fundamentals. It begins with system modeling using the state-space approach, explaining how physical systems can be represented using state variables. Learners will study state equations, state transition matrices, and different methods to solve state-space models.A significant part of the course is devoted to stability analysis in the state-space framework, helping students understand how system behavior changes over time and how stability can be assessed mathematically. The course then moves on to important system properties such as controllability and observability, which are essential for effective control system design.Further, learners will explore controller design and observer design techniques, enabling them to design systems that meet desired performance requirements even when all state variables are not directly measurable. Throughout the course, theoretical concepts are reinforced using numerical problems, practical engineering examples, and MATLAB programming, making it easier to connect theory with real-world applications.Overall, this course equips students, researchers, and practicing engineers with the analytical and practical skills needed to model, analyze, and design advanced control systems confidently.

Source: IIT Roorkee July 2018 [Youtube Channel]

Course suitable for

  • Automotive
  • Electronics & Instrumentation
  • Electrical
  • Engineering & Design
  • Project Management
  • Research & Developmnet

Key topics covered

  • Advanced Linear Continuous Control Systems

  • Introduction to State Space

  • State Space Representation

  • State Space Representation: Companion Form (Controllable Canonical Form)

  • State Space Representation: Extended Controllable Canonical Form

  • State Space Representation: Observable Canonical Form

  • State Space Representation: Diagonal Canonical Form (Part-I)

  • State Space Representation: Diagonal Canonical Form (Part-II)

  • State Space Representation: Jordan Canonical Form

  • State Space Representation: Numerical Examples on State space Modelling (Part-I)

  • State Space Representation: Numerical Examples on State space Modelling (Part-II)

  • Modelling of Mechanical Systems in State Space

  • Modelling of DC Servo Motor (Part-I)

  • Modelling of DC Servo Motor (Part-II)

  • Determination of Transfer Function from State Space Model (Part-II)

  • Determination of Transfer Function from State Space Model (Part-I)

  • Stability Analysis in State Space (Part-II)

  • Stability Analysis in State Space: Concept of Eigenvalues and Eigenvectors (Part-I)

  • Stability Analysis in State Space: Lyapunov Stability Analysis (Direct Method) Part-V

  • Stability Analysis in State Space: Lyapunov Stability Analysis (Stability Criterion) Part-IV

  • Stability Analysis in State Space: Lyapunov Stability Analysis (Sylvester’s Criterion) Part-III

  • Concept of Diagonalization

  • Solution of State Equation

  • Solution of State Equation (Forced System)

  • State Transition Matrix (Part-I)

  • Steady State Error for State Space System

  • State Transition Matrix (Part-II)

  • State Transition Matrix using Cayley-Hamilton Theorem (Part-III)

  • Controllability in State Space (Part-I)

  • MATLAB Programming with State Space

Why people choose EveryEng

Industry-aligned courses, expert training, hands-on learning, recognized certifications, and job opportunities—all in a flexible and supportive environment.

Engineering Academy

Engineering Academy

Learn Without Limits: Free Engineering Courses

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