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Related Concept Videos

Linear time-invariant Systems01:23

Linear time-invariant Systems

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 calculated...
Open and closed-loop control systems01:17

Open and closed-loop control systems

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 and...
Load-frequency control01:28

Load-frequency control

Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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.
Control Systems: Applications01:25

Control Systems: Applications

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.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The direction...
LC Circuits01:21

LC Circuits

An LC circuit consists of an inductor and a capacitor, either in series or parallel. Consider a charged capacitor connected with an inductor in series. Before the switch is closed, all the energy of the circuit is stored in the electric field of the capacitor. When the switch is closed, the capacitor begins to discharge, producing a current in the circuit. The current, in turn, creates a magnetic field in the inductor. Because of the induced emf in the inductor, the current cannot change...

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Related Experiment Videos

LLM-Conductor: A Closed-Loop Resource-Adaptive Architecture for Secure LLM Deployment in Industrial Sensor Networks

Kai Xu1, Diming Zhang1, Xuguo Wang2

  • 1School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212100, China.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

LLM-Conductor enhances industrial large language model (LLM) deployment by improving decision-making, memory reuse, and resource scheduling, significantly reducing security risks and boosting task completion rates.

Keywords:
LLM securityclosed-loop controlindustrial deploymentindustrial environment simulation and adaptationresource optimization

Related Experiment Videos

Area of Science:

  • Artificial Intelligence
  • Computer Science
  • Industrial Internet of Things

Background:

  • Industrial LLM deployment faces challenges including decision-making gaps, limited experience reuse, and fragmented resource scheduling.
  • These issues hinder efficiency, security, and reliability in industrial applications.

Purpose of the Study:

  • To introduce LLM-Conductor, a novel three-layer collaborative architecture for industrial LLM deployment.
  • To address bottlenecks in autonomous decision-making, structured policy memory, and joint resource optimization.

Main Methods:

  • Developed a three-layer collaborative architecture (LLM-Conductor).
  • Conducted ablation studies, horizontal comparisons with ISOLATEGPT and ReAct, and resource-reduction experiments.
  • Validated performance under simulated resource-constrained environments.

Main Results:

  • Security risk incidence reduced from 70.6% to 1.3%.
  • Multi-application collaborative task completion rate reached 100%.
  • Token utilization improved to 88.9%, with core task completion >95% under resource constraints (≥512 MB RAM, ≥0.5 GHz CPU).

Conclusions:

  • LLM-Conductor offers an integrated solution for efficient, secure, and reliable LLM deployment in Industrial IoT.
  • Deeply coupling decision-making and resource scheduling is key to optimizing LLM performance.
  • Future work will focus on physical-layer industrial integration.