ELEC4632 Chap.4 Digital Controllers and Output Feedback
Digital Controllers and Output Feedback
The laboratory distinguishes regulation from set-point control and then implements both observer-based state feedback and digital PID on the water-tank process. This chapter treats controller choice as a requirements decision.
It explains deviation variables and operating-point offsets, compares PID with model-driven deadbeat design, and follows the laboratory workflow from process knowledge through simulation, platform selection and real-time verification.
What this chapter covers
- 01
Regulation as return to an equilibrium point
- 02
Set-point control as tracking a desired physical level
- 03
Deviation variables and restoration of input-output offsets
- 04
Reference scaling and closed-loop steady-state mapping
- 05
Digital PID error actions and integral windup risk
- 06
Deadbeat response and sensitivity to model or actuator limits
- 07
Simulation, platform selection and hardware verification
Worked example · free
Implement a deviation-model controller on the physical plant
- +1Subtract the output operating offset from the physical reference and measurement.
- +1Compute the deviation command using the designed controller and available state estimate.
- +1Add the input operating offset before sending the command to the actuator.
- +1Compare physical reference and output while checking steady-state offset, saturation and signal range.
Key terms
- Regulation
- Regulation drives a disturbed process variable back toward its equilibrium value.
- Set-Point Control
- Set-point control moves an output toward a specified reference and maintains it there.
- Deviation Variable
- A deviation variable measures a signal relative to its chosen operating-point value.
- Integral Windup
- Integral windup is accumulated integral action while an actuator cannot deliver the requested command.
- Reference Scaling
- Reference scaling compensates for the closed-loop steady-state map between a command and the achieved output.
Digital Controllers and Output Feedback FAQ
How do regulation and set-point control differ?
Regulation removes a deviation and returns the process to equilibrium. Set-point control moves the process to a specified reference and must address steady-state tracking. The same plant can perform both tasks, but the reference handling and performance evidence differ.
Why are operating offsets important in implementation?
A controller designed around deviations assumes zero corresponds to the selected operating point. Physical sensors and actuators use nonzero values, so offsets must be removed and restored at the interface. Otherwise the controller acts on incorrectly interpreted signals.
What should be compared after real-time implementation?
Plot the reference, measured output and actual control input, then compare them with simulation under the same configuration. Check tracking or regulation, input limits, timing, noise and any persistent offset before changing gains.
When is reference scaling relevant?
If a closed-loop state-feedback model maps a constant command to a steady output with gain other than one, a reference factor can align the requested physical target with the modelled equilibrium. Compute it from the identified plant rather than assuming unity tracking.
How do PID and deadbeat designs differ in emphasis?
PID organises proportional, accumulated-error and error-change actions and can remove persistent offset through integral action. Deadbeat design targets a finite-sample model response. Compare their model dependence, input demand and sensitivity instead of treating either label as a complete performance guarantee.
Why plot the input with the controlled output?
An output can appear to track well while the actuator is saturated or operating outside the identified range. The command trace shows whether the response is physically credible and helps distinguish tuning limits from offset, model or instrumentation problems.
Exam move
Build a two-column summary of regulation and set-point control, then label where offsets enter the measurement and actuator paths. Compare PID and deadbeat design by model dependence, steady-state behaviour, control effort and sensitivity. For the laboratory, memorise the process order: understand inputs and outputs, identify a model, specify requirements, design, simulate, choose a platform and implement.
Practise explaining why each stage precedes the next. Draw the interface twice: once in physical variables and once in deviation variables. Mark the equilibrium level, sensor offset, actuator offset and reference conversion so each addition or subtraction has a physical meaning. Then trace one constant set-point through the blocks and predict the steady output before running a simulation.
For controller comparisons, use the same headings every time: objective, plant information, expected transient, steady-state behaviour, input demand and implementation sensitivity. Do not decide from output shape alone; always inspect the actual command and any saturation. Rehearse a mismatch diagnosis that begins with units, channels, signs and offsets, then moves to timing, modelling range and tuning.
Keep screenshots or plots paired with the exact model and controller version that produced them. In an exam answer, distinguish regulation from tracking in the first sentence, state how the reference enters and close by naming the output and input evidence needed to verify the claim on the water-tank process.
Run a paper trace of one sample: convert the physical measurement to deviation form, apply the controller, restore the actuator offset and check the resulting command range. Repeat with a changed reference so reference scaling is visible. Use the trace to identify exactly where a sign or offset error would appear in the plots. This provides a practical bridge between algebraic feedback laws and the real-time interface.
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