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関連する概念動画

Feedback control systems01:26

Feedback control systems

657
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
657
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

314
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
314
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

329
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
329
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

345
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.
Consider the example of control of motor torque. Initially, a positive...
345
Second Order systems II01:18

Second Order systems II

367
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
367
Linear time-invariant Systems01:23

Linear time-invariant Systems

839
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
839

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非線形システムにおける反復依存期間を対象としたデータ駆動型反復学習制御

Yuxin Wu1, Deyuan Meng2, Jian Sun3

  • 1National Key Laboratory of Autonomous Intelligent Unmanned Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, PR China.

ISA transactions
|December 28, 2025
PubMed
まとめ
この要約は機械生成です。

本研究では、期間が変動する非線形システムに対するデータ駆動型反復学習制御（ILC）を提案する。新しいILC更新則により、システムデータを利用して完全な追従を実現する。

キーワード:
データ駆動制御反復依存期間反復学習制御局所リプシッツ連続非線形性

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科学分野:

  • 制御工学
  • 非線形システムダイナミクス
  • 制御のための機械学習

背景:

  • 反復学習制御（ILC）は反復タスクに不可欠である。
  • 局所リプシッツ連続非線形システムは、複雑なダイナミクスにより課題をもたらす。
  • 反復依存期間は、従来のILCアプローチを複雑にする。

研究 の 目的:

  • 反復依存期間を有する局所リプシッツ連続非線形システムのためのデータ駆動型ILC戦略を開発する。
  • 収集された入出力データを効果的に利用するILC更新則を設計する。
  • このようなシステムで完全な追従を達成するための条件を確立する。

主な方法:

  • 反復ごとの入出力データを収集するためのテストフレームワーク。
  • 期間変動に対抗するために修正出力を統合するILC更新則。
  • 永続的完全学習特性に基づく解析。

主要な成果:

  • 非線形システムのためのデータ駆動型ILC更新則を提案する。
  • この手法は、反復依存期間を効果的に補償する。
  • 出力データに基づき、完全な追従のための必要十分条件を導出する。

結論:

  • 開発されたデータ駆動型ILCは、局所リプシッツ連続非線形システムおよび不規則なダイナミクスに適用可能である。
  • このアプローチは、変動する動作長さを有するシステムに対する堅牢なソリューションを提供する。
  • 提案されたデータ依存条件の下で完全な追従が可能である。