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Related Concept Videos

PD Controller: Design01:26

PD Controller: Design

304
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.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
304
Open and closed-loop control systems01:17

Open and closed-loop control systems

849
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
849
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

153
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...
153
Feedback control systems01:26

Feedback control systems

358
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...
358
Controller Configurations01:22

Controller Configurations

128
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
128
PI Controller: Design01:24

PI Controller: Design

388
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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Related Experiment Video

Updated: Aug 4, 2025

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot
07:40

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Adaptive control of a soft pneumatic actuator using experimental characterization data.

Yoeko Xavier Mak1, Hamid Naghibi1, Yuanxiang Lin1

  • 1Robotics and Mechatronics Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Technical Medical (TechMed) Centre, University of Twente, Enschede, Netherlands.

Frontiers in Robotics and AI
|April 3, 2023
PubMed
Summary

This study introduces an adaptive control method for fiber reinforced soft pneumatic actuators, addressing their complex non-linear behaviors. The data-driven approach enables precise control, compensating for fabrication inconsistencies and improving trajectory following.

Keywords:
adaptive controldata-driven control (DDC)experimental characterisationfiber reinforced actuatorsminimally invasive surgery (MIS)pneumatic actuator

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Area of Science:

  • Robotics
  • Materials Science
  • Control Systems

Background:

  • Fiber reinforced soft pneumatic actuators (FSPAs) exhibit challenging non-linear and non-uniform behaviors.
  • Traditional model-based and model-free control methods struggle with FSPA complexities.

Purpose of the Study:

  • To design, fabricate, characterize, and control a 12 mm outer diameter FSPA.
  • To develop an adaptive, data-driven control strategy for precise FSPA manipulation.

Main Methods:

  • Characterization data was used to map actuator input pressures to spatial angles.
  • Mapping functions informed adaptive feedforward and feedback control signal generation.
  • The control system adjusted parameters based on the actuator's bending configuration.

Main Results:

  • The adaptive controller successfully followed a 2D tip orientation reference trajectory.
  • Achieved mean absolute errors of 0.68° for bending angle magnitude and 3.5° for axial bending phase.
  • Demonstrated effective compensation for non-uniform and non-linear FSPA behavior.

Conclusions:

  • A data-driven adaptive control method offers an intuitive solution for FSPAs.
  • This approach effectively manages the inherent non-linearities and non-uniformities of FSPAs.
  • The developed method enhances the precision and reliability of soft robotic actuators.