A Practical Introduction to Digital Process Control for dsPIC developers

Overview
To take advantage of the Digital Control capabilities of the dsPIC architecture a sound understanding of the principles and practice of Digital Control and related DSP processing is Required. This 5 day course avoids digging deep into the theory and maths. Rather it aims to provide a sound understanding of the principles, and techniques needed to design effective Digital Control Systems. Its goal is to ensure that engineers learn how to select and parameterize the most appropriate Digital Control Algorithms for the task at hand.

Key Skills
After attending this course, you will be able to:

• Understand the basic theory and principles underlying control systems
• Learn how to move from the design of an analog control system to the design of the corresponding digital control system
• Be aware of the assumptions and design issues involved in implementing digital control systems
• Understand the basics of process oriented modeling in the design and implementation of Digital Control Systems
• Learn the principles of robust control design

Course Contents
Overview of computer control theory Overview of discrete time systems

• sampling continuous time signals
• sampling continuous time state-space systems
• sampling systems with time delays
• an overview of difference equations
• input-output models
• overview of Z-transform, poles and zeros

Analysis of discrete time systems

• stability
• sensitivity
• robustness
• controlability
• reachability
• observability
• detectability

Pole placement design techniques Structuring complex systems Process oriented modeling

• modulation model
• frequency response
• pulse-transfer function

Approximating Continuous Time Controllers

• approximations based on transfer functions
• approximations based on state models
• frequency design approaches
• digital PID controllers

Implementing Digital Controllers

• pre-filtering
• taking computational delay into account
• handling non-linear actuators
• programming the implementation of digital controllers

Disturbances

• piecewise deterministic models
• stochastic models

State space and polynomial approaches to Optimal Design Identification