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Related Concept Videos

Control Systems01:10

Control Systems

1.3K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
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Open and closed-loop control systems01:17

Open and closed-loop control systems

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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.
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Controller Configurations01:22

Controller Configurations

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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.
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Control Systems: Applications01:25

Control Systems: Applications

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
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Feedback control systems01:26

Feedback control systems

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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...
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Mechanical Systems01:22

Mechanical Systems

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Mechanical systems are analogous to to electrical networks where springs and masses play similar roles to inductors and capacitors, respectively. A viscous damper in mechanical systems functions similarly to a resistor in electrical networks, dissipating energy. The forces acting on a mass in such systems include an applied force in the direction of motion, counteracted by forces from the spring, a viscous damper, and the mass's acceleration. This interplay of forces is mathematically...
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Flexible skill-based control for robot cells in manufacturing.

Torben Wiese1, Johannes Abicht1, Christian Friedrich1

  • 1IIoT Controls and Technical Cybernetics, Fraunhofer Institute for Machine Tools and Forming Technology, Dresden, Germany.

Frontiers in Robotics and AI
|October 17, 2022
PubMed
Summary
This summary is machine-generated.

Flexible automation is crucial for manufacturing. This study introduces a skill-based control method for robot cells, enabling operators to adapt processes without reprogramming, enhancing flexibility and efficiency.

Keywords:
flexible control systemsmodular automationrobot cellsrobot skillsskill-based control

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Area of Science:

  • Robotics
  • Automation Engineering
  • Manufacturing Systems

Background:

  • Decreasing batch sizes necessitate more flexible automation in manufacturing.
  • Current robot cell controllers require specialized expertise for reprogramming, limiting adaptability.
  • Existing systems lack non-uniform programming, hindering process changes.

Purpose of the Study:

  • To present a novel method for programming flexible skill-based controls for robot cells.
  • To enable operators to adapt and expand automated process sequences without controller code modification.
  • To define software requirements for high flexibility: extensibility, usability, configurability, and reusability.

Main Methods:

  • Introduced modularization of assets and parameterizable skills as abstract template methods.
  • Developed an orchestration system to combine skills into automated process sequences.
  • Validated the skill-based control architecture using a mobile flexible robot cell.

Main Results:

  • Operators can independently adapt and expand automated process sequences.
  • The skill-based control offers enhanced flexibility, configurability, and reusability.
  • Successful validation demonstrated the feasibility of the proposed control architecture.

Conclusions:

  • The skill-based control method significantly improves the flexibility of robot cells.
  • This approach empowers operators, reducing reliance on specialized programming expertise.
  • Future work should address challenges in scaling and implementing flexible skill-based controls.