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Event Brief

This course deals with the design of practical control algorithms for linear and nonlinear dynamic processes that are described by state-space mathematical models.   The “observer-based” design method is emphasized, in which the control algorithm is designed in two distinct steps: full-state feedback design, and observer design.  Full-state feedback is based on the assumption that all process state variables can be measured or estimated, and the observer is designed to provide estimates of the state variables based on the available measurements.

Topics to be covered included the extended linearization, bounded control including pulse-width and pulse frequency modulation, Kalman filters as optimum observers, friction and other “parasitic” nonlinearities.

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Course Objective
  • Become familiar with recent model- based design techniques for   control algorithms in various systems (mechatronic, robotic, and aerospace.)
  • Develop skill at designing control algorithms for linear and nonlinear processes.
  • Understand how to design Kalman filters for various applications.
  • Become adept at use of Matlab, Simulink, and other toolboxes performing design calculations and simulating system behavior
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    Course Agenda

    For more details on course agenda, please click here

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    Who Should Attend
  • Control system engineers with classical (linear) control system background who are interested in learning about recently-developed methods for nonlinear systems, or with controls of limited authority.
  • Engineering managers who desire to broaden the scope of their control system design knowledge.
  • Professors desiring to enhance their control system courses.
    • Note: Attendees should have a basic knowledge of feedback control system theory such as is covered in an undergraduate course, or through experience in design of feedback control systems.
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    Training Venue
    To be updated
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    Contact Us

    For more information about the event, please contact +65 8363 3065 or email marketing@k2binternational.com

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