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Time-Domain Interpretation of PD Control01:07

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Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
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In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
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First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
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Updated: May 6, 2026

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Performance limitations in the tracking and regulation problem for discrete-time systems.

Xiao-Wei Jiang1, Zhi-Hong Guan2, Fu-Shun Yuan3

  • 1College of Automation, Huazhong University of Science and Technology, Wuhan 430074, PR China; College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi 435002, PR China.

ISA Transactions
|October 29, 2013
PubMed
Summary

This study investigates optimal control for discrete-time systems, considering disturbances and noise. Performance depends on system zeros, poles, and external factors like disturbance and additive white Gaussian noise (AWGN).

Keywords:
MIMO discrete-time systemsNonminimum phase zerosOutput regulationReference trackingUnstable poles

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Area of Science:

  • Control Systems Engineering
  • Systems Theory
  • Signal Processing

Background:

  • Investigates discrete-time, multi-input multi-output, linear time-invariant systems.
  • Addresses control signal influence by external disturbance.
  • Considers output feedback corrupted by additive white Gaussian noise (AWGN).

Purpose of the Study:

  • Determine optimal tracking and regulation performance.
  • Analyze performance metrics under input power and control energy constraints.
  • Identify factors influencing system performance.

Main Methods:

  • Searches through all stabilizing two-parameter controllers.
  • Adopts tracking error with channel input power constraint as a performance measure.
  • Adopts output regulation with control energy constraint as a performance measure.

Main Results:

  • Optimal performance is linked to nonminimum phase zeros and unstable poles.
  • External disturbance and AWGN significantly degrade performance.
  • Performance is sensitive to the location and direction of system zeros and poles.

Conclusions:

  • System performance is fundamentally limited by its internal dynamics (zeros and poles).
  • External disturbances and sensor noise are critical factors impacting achievable control performance.
  • Controller design must account for these inherent system properties and external influences.