Professional Diploma Control and Systems Engineering

Categories: Technical Courses
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About Course

Control engineering or control systems engineering is an engineering discipline that deals with control systems, applying control theory to design equipment and systems with desired behaviors in control environments.

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Course Curriculum

1. Control Fundamentals

  • Laplace transform and inverse Laplace transform
    10:38
  • Analysis of single-input single-output control structures, including open-loop, closed-loop, feedforward and two-degree-of-freedom control structures.
    18:13
  • Analysis of step/impulse responses of first and second order dynamic systems
  • Design and tuning of proportional control, PI control, PD control and PID control
  • Interpretation of root locus
  • Frequency response, including direct measurement of responses
  • Assignments

2. State-Space and Multivariable Control

  • Introduction to state variables, order and state equations
  • State space modelling of dynamical systems – applications and examples
  • Controllable canonical form and observer canonical form
  • State space realisation of transfer functions
  • State transition matrix, matrix exponential and time response of state space models
  • Modal form, modal behaviour and system dynamics
  • Assignments

3. Digital Control & System Identification

  • Motivation for digital control theory, including computer-based control
  • Stability analysis
  • Classical analysis in the discrete domain
  • Exemplar system identification problems
  • Measurements and Statistics
  • Least square problem Statistic foundation
  • Assignments

4. Nonlinear and Adaptive Control Systems

  • Characteristics of nonlinear behaviour, linearized models
  • Phase-plane methods; approximate construction of state trajectories
  • Describing functions; use in predicting oscillations
  • Compensation for nonlinearities; feedback linearization
  • Integrator backstepping and iterative backstepping design
  • Adaptive control of nonlinear systems and adaptive backstepping
  • Assignments

5. Process Control & Model Predictive Control

  • PID controller structure: ideal/parallel/series, position/velocity implementation of digital PID
  • PID controller tuning: Ziegler-Nichols and Cohen-Coon, Internal Model Control with lambda-tuning
  • Enhanced control: cascade control, feedforward control, multi-loop control utilising de-couplers, Smith Predictor
  • Multi-loop interaction analysis using Relative Gain Array
  • Real-time process optimisation using Linear Programming technique
  • Assignments

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