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Servomechanism Course
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Servomechanism Course

Master the complete engineering discipline of servomechanism design, from feedback control fundamentals to advanced digital and adaptive strategies. This course equips you with the analytical tools and practical techniques used by motion control engineers across industrial, robotics, and automation sectors. Whether you are advancing your career or deepening your technical expertise, this is the definitive resource for servo system mastery.

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What you will learn:

You will build a rigorous understanding of closed-loop control principles and apply mathematical modelling techniques to real servo systems. The course covers time-domain and frequency-domain analysis, stability criteria, and compensator design using both classical and modern methods. You will study the hardware side of servo systems, including DC and AC motors, encoders, resolvers, and PWM drive amplifiers. Advanced topics include feedforward control, disturbance observers, cascade loop architectures, and digital discretisation. You will also explore motion profiling, system commissioning, functional safety, and emerging technologies such as machine learning-based tuning and industrial IoT connectivity.

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Course content

8 Chapters • 37 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Servomechanism Systems

  • Lesson 1 • Physical Units and System Variables

    Establishes the physical quantities—position, velocity, torque, and current—used in servo analysis. Provides unit consistency for later mathematical modelling.

  • Lesson 2 • Core Components of a Servomechanism

    Identifies actuators, sensors, controllers, and plant elements within a servo loop. Connects each component to its functional role.

  • Lesson 3 • Introduction to Control Systems

    Defines open-loop vs. closed-loop control and establishes why feedback is essential. Sets the vocabulary used throughout the course.

  • Lesson 4 • Signal Flow and Block Diagrams

    Introduces block diagram notation to represent signal paths in servo systems. Students trace error signals from reference input to output.

Chapter 2See details

Mathematical Modelling of Servo Systems

  • Lesson 1 • Laplace Transform and Transfer Functions

    Converts time-domain differential equations into s-domain transfer functions. Enables algebraic manipulation of system dynamics.

  • Lesson 2 • Differential Equations for Mechanical Systems

    Applies Newton's laws to derive equations of motion for rotational and translational loads. Establishes the mathematical foundation for transfer function derivation.

  • Lesson 3 • Electrical Circuit Modelling

    Models DC motor armature circuits and amplifier stages using Kirchhoff's laws. Links electrical dynamics to mechanical load equations.

  • Lesson 4 • Model Validation and Simplification

    Compares model predictions against measured data and applies order-reduction techniques. Ensures models are accurate yet computationally tractable.

  • Lesson 5 • State-Space Representation

    Formulates servo dynamics as state-variable equations for multi-input, multi-output analysis. Bridges classical and modern control approaches.

Chapter 3See details

Time-Domain Performance Analysis

  • Lesson 1 • Standard Test Inputs and System Response

    Defines step, ramp, and parabolic inputs and derives the corresponding output responses. Provides a consistent basis for comparing system performance.

  • Lesson 2 • Steady-State Error Analysis

    Calculates position, velocity, and acceleration error constants for different system types. Determines how system type affects tracking accuracy.

  • Lesson 3 • Transient Response Specifications

    Quantifies rise time, peak time, overshoot, and settling time from step responses. Connects these metrics to damping ratio and natural frequency.

  • Lesson 4 • Effects of Poles and Zeros on Response

    Examines how pole and zero locations in the s-plane shape transient behaviour. Guides controller design by linking pole placement to performance specs.

Chapter 4See details

Frequency-Domain Analysis Techniques

  • Lesson 1 • Gain and Phase Margin Evaluation

    Defines gain margin and phase margin as quantitative stability indicators. Establishes minimum margin guidelines for robust servo operation.

  • Lesson 2 • Nyquist Stability Criterion

    Applies the Nyquist criterion to determine closed-loop stability from open-loop frequency response. Handles systems with right-half-plane poles and time delays.

  • Lesson 3 • Sensitivity and Complementary Sensitivity

    Introduces sensitivity functions to quantify disturbance rejection and robustness. Connects loop shaping objectives to sensitivity function bounds.

  • Lesson 4 • Bode Plot Construction and Interpretation

    Constructs magnitude and phase Bode plots from transfer functions using asymptotic approximations. Identifies gain crossover and phase crossover frequencies.

  • Lesson 5 • Closed-Loop Frequency Response

    Derives bandwidth, resonant peak, and resonant frequency from closed-loop Bode plots. Links frequency-domain specs to time-domain performance metrics.

Chapter 5See details

Stability Analysis and Root Locus

  • Lesson 1 • Gain Selection Using Root Locus

    Selects controller gain to achieve desired damping ratio and natural frequency on the root locus. Verifies performance specs through closed-loop pole placement.

  • Lesson 2 • Root Locus for System Design

    Extends root locus to evaluate the effect of adding poles and zeros via compensators. Prepares students for controller design in the following chapter.

  • Lesson 3 • Root Locus Construction Rules

    Derives the rules governing root locus branches as gain varies from zero to infinity. Enables graphical prediction of closed-loop pole trajectories.

  • Lesson 4 • Routh-Hurwitz Stability Criterion

    Applies the Routh array to determine the number of unstable closed-loop poles algebraically. Provides a quick stability check without computing roots explicitly.

Chapter 6See details

Servo Controller Design and Compensation

  • Lesson 1 • Lead-Lag and Notch Compensation

    Combines lead and lag elements to simultaneously improve transient response and steady-state accuracy. Introduces notch filters for resonance suppression.

  • Lesson 2 • State Feedback and Pole Placement

    Designs full-state feedback controllers by placing all closed-loop poles at specified locations. Introduces integral augmentation for zero steady-state error.

  • Lesson 3 • PID Controller Structure and Tuning

    Explains proportional, integral, and derivative actions and their individual effects on servo response. Covers Ziegler-Nichols and analytical tuning methods.

  • Lesson 4 • Lag Compensator Design

    Designs phase-lag networks to improve steady-state accuracy without significantly reducing stability margins. Addresses low-frequency gain enhancement.

  • Lesson 5 • Lead Compensator Design

    Designs phase-lead networks to increase phase margin and improve transient response speed. Uses both root locus and Bode plot approaches.

Chapter 7See details

Servo Actuators, Sensors, and Drives

  • Lesson 1 • AC Servo Motors and Drives

    Describes permanent-magnet synchronous and induction motor servo drives and their vector control principles. Links drive output to closed-loop position and velocity control.

  • Lesson 2 • Drive Amplifier Selection and Interfacing

    Covers PWM amplifier topologies, current limiting, and analogue/digital command interfaces. Guides students through drive commissioning and protection setup.

  • Lesson 3 • DC and Brushless DC Servo Motors

    Compares brush-type and brushless DC motors in terms of torque-speed characteristics and control complexity. Covers winding configurations and thermal ratings.

  • Lesson 4 • Position and Velocity Feedback Sensors

    Evaluates encoders, resolvers, tachometers, and linear scales for position and velocity feedback. Addresses resolution, accuracy, and signal conditioning.

  • Lesson 5 • Mechanical Transmission Elements

    Analyses gearboxes, ball screws, and belt drives as load-coupling elements affecting servo dynamics. Quantifies backlash, compliance, and inertia reflected to the motor.

Chapter 8See details

Advanced Servo Control Strategies

  • Lesson 1 • Adaptive and Gain-Scheduling Control

    Introduces parameter adaptation and gain scheduling to handle varying load inertia and friction. Covers model reference adaptive control structure for servo applications.

  • Lesson 2 • Disturbance Observers and Friction Compensation

    Designs disturbance observers to estimate and reject torque disturbances in real time. Applies friction models to compensate for Coulomb and Stribeck effects.

  • Lesson 3 • Digital Control and Discretization

    Converts continuous controllers to discrete-time implementations using z-transform methods. Addresses sampling rate selection, quantisation, and computational delay.

  • Lesson 4 • Cascade and Multi-Loop Control

    Structures position, velocity, and current loops in a cascade hierarchy to improve disturbance rejection and bandwidth. Establishes bandwidth separation rules between loops.

  • Lesson 5 • Feedforward and Model-Based Control

    Adds feedforward paths based on inverse system models to reduce tracking error without sacrificing stability. Demonstrates velocity and acceleration feedforward implementation.

Certification

Your valid completion certificate

This course is for you:

  • Electrical engineer: wants structured theory behind the servo systems they configure.

  • Mechanical engineer: needs control knowledge to collaborate effectively on mechatronics projects.

  • Automation technician: ready to move from hands-on wiring into engineering-level analysis.

  • Robotics developer: building motion systems and needs rigorous closed-loop design skills.

  • Recent engineering graduate: bridging the gap between coursework and industrial servo practice.

  • Career changer: transitioning into motion control from adjacent technical or manufacturing roles.

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