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Related Concept Videos

Time and frequency -Domain Interpretation of Phase-lag Control01:21

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Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
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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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Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
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PD Controller: Design01:26

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Related Experiment Video

Updated: Feb 25, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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Throughput and latency programmable optical transceiver by using DSP and FEC control.

Takahito Tanimura, Takeshi Hoshida, Tomoyuki Kato

    Optics Express
    |August 10, 2017
    PubMed
    Summary
    This summary is machine-generated.

    We developed a programmable optical transceiver that optimizes multiple parameters for better performance. This system efficiently finds optimal settings, reducing complexity for applications needing high throughput and low latency.

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    Area of Science:

    • Optical communication systems
    • Photonics and optoelectronics
    • Signal processing

    Background:

    • Optimizing optical transceivers involves balancing multiple parameters like modulation format, symbol rate, and power allocation.
    • The combinatorial complexity of these parameters hinders efficient optimization for diverse network requirements.
    • Existing methods struggle to simultaneously address throughput, signal quality, and latency demands.

    Purpose of the Study:

    • To propose and demonstrate a programmable optical transceiver capable of simultaneous multi-parameter optimization.
    • To develop a method for efficiently finding feasible parameter combinations, overcoming combinatorial explosion.
    • To enable optical transceivers that adapt to varying requirements for throughput, signal quality, and latency.

    Main Methods:

    • Developed a precise analytical model to predict Bit Error Rate (BER) based on Optical Signal-to-Noise Ratio (OSNR), modulation formats, symbol rates, and power differences.
    • Formulated parameter constraints and integrated them with the analytical model to identify optimal parameter sets.
    • Implemented and experimentally validated the end-to-end transceiver operation, including Low-Density Parity-Check (LDPC) Forward Error Correction (FEC).

    Main Results:

    • Successfully demonstrated a proof-of-concept programmable optical transceiver.
    • The proposed method effectively reduces the search space for optimal parameter combinations.
    • Experimental validation confirmed the transceiver's ability to meet latency-sensitive application requirements over 40-km transmission.

    Conclusions:

    • The programmable optical transceiver offers a viable solution for optimizing complex optical communication systems.
    • The integrated analytical model and constraint formulation efficiently identify feasible operating parameters.
    • This approach enhances adaptability and performance for future optical networks, particularly for latency-critical applications.