2. Agenda
What is Digital Control?
Examples of Digitally Controlled Systems
Classical Control Systems
Digital Control Systems
2
3. What is Digital Control?
Automatic control is the science that develops techniques to steer, guide,
control dynamic systems.
Examples of such dynamic systems are found in biology, physics, robotics,
finance, etc.
Digital Control means that the control laws are implemented in a digital
device, such as a microcontroller or a microprocessor. Such devices are light,
fast and economical.
Digital control systems = “Digital signals” + ”Control systems”
The points that will be examined in these lecture notes are the following:
transformation of an already designed continuous-time controller into a discrete-
time controller,
discretization of continuous systems,
direct synthesis of discrete-time control systems,
practical considerations and precautions when implementing a digital controller.
3
4. Examples of Digitally Controlled Systems
Nowadays, digitally controlled systems are everywhere,
automotive industry: speed regulators in cars,
aeronautic/space industry: autopilots, automatic take off/landing, cruise
control
chemistry: pharmaceutical industries, oil transformation, liquid level in
tanks
robotics: robot-arm trajectory control, manipulation,
housing: in-house temperature regulation
4
5. Classical Control Systems
Objective:
1) Closed-loop stable
2) Small steady-state error
3) Good transient response
4) Disturbance rejection
Analog Controllers difficult to modify or redesign once implemented
in hardware
5
6. Digital Control Systems
A/D Converter: change analog signal to digital signal
D/A Converter: change digital signal to analog signal
Digital controller: implemented in digital computers, or in
microprocessors
Sensors: monitors controlled variable for feedback.
Plant: the analog system to be controlled. 6
7. Simplified version of a digital control systems
Sampler:
Zero-order-Hold:
C(z): Discrete-Time Controller to be designed.
7
8. Why Digital Control?
Easy to implement complicated control algorithms
Easy to modify the controller
Controller parameters unchanged with variations in environment
Low cost, low weight, and low power dissipation
High noise tolerance
8
9. Disadvantages
Sampling and quantization process will degrade system performance
Software errors
Need power supply
9