adrc

v1.0.2 safe
1.0
Low Risk

Active Disturbance Rejection Control (ADRC) with Tracking Differentiator

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity based on the provided analysis notes. It does not engage in network calls, shell executions, or any form of obfuscation that could indicate hidden malicious intent.

  • No network calls detected
  • No shell execution detected
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution detected, indicating no immediate risk of command injection or similar attacks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 3.0

Possible typosquat of: arq

  • "adrc" is 2 edit(s) from "arq"
⚠ Registered Email Domain score 3.0

Suspicious email domain flags: Very short email domain: ee.sharif.edu>

  • Very short email domain: ee.sharif.edu>
✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository MRGilak/Active-Disturbance-Rejection-Controller appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with adrc 
Create a Python-based mini-application that leverages the 'adrc' package to simulate and visualize the effectiveness of Active Disturbance Rejection Control (ADRC) in real-time systems. This application should allow users to input different types of disturbances and observe how ADRC mitigates their impact on system performance. Here’s a detailed breakdown of the application’s requirements:

1. **System Setup**: Define a basic dynamic system model that can represent a variety of physical systems such as mechanical, electrical, or thermal systems.
2. **Disturbance Input**: Allow users to introduce various types of disturbances (e.g., step, sinusoidal, random noise) into the system.
3. **ADRC Implementation**: Utilize the 'adrc' package to implement the ADRC control strategy. This includes setting up the tracking differentiator and the extended state observer (ESO).
4. **Real-Time Simulation**: Develop a real-time simulation environment where the user can observe the system’s response to disturbances both with and without ADRC.
5. **Visualization Tools**: Implement graphical tools to visualize the system’s behavior over time. This should include plots showing the system output, the estimated disturbance, and the control effort.
6. **Performance Analysis**: Include features that analyze the system’s performance under ADRC, such as calculating the steady-state error, overshoot, and settling time.
7. **User Interface**: Design a simple yet intuitive GUI using libraries like Tkinter or PyQt to make the application accessible and user-friendly.
8. **Documentation and Testing**: Provide comprehensive documentation for each component of the application and ensure thorough testing to validate the ADRC implementation.

By following these steps, you will create an educational and practical tool that demonstrates the power of ADRC in enhancing system robustness against disturbances.