Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

PI Controller: Design01:24

PI Controller: Design

1.3K
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...
1.3K
PD Controller: Design01:26

PD Controller: Design

679
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,...
679
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

444
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
444
Controller Configurations01:22

Controller Configurations

399
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...
399
PID Controller01:19

PID Controller

777
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
777
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

873
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
873

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Toward Industry 5.0: A WebSocket-S7 Bridge for Low-Latency, IEC 61588-Compliant Digital Twins in Remote Industrial Automation.

PloS one·2026
Same author

Generalized q-Method Relative Pose Estimation for UAVs with Onboard Sensor Measurements.

Sensors (Basel, Switzerland)·2025
Same author

Enhancing unity-based AR with optimal lossless compression for digital twin assets.

PloS one·2024
Same author

Software defined radio frequency sensing framework for intelligent monitoring of sleep apnea syndrome.

Methods (San Diego, Calif.)·2023
Same author

Enhancing System Performance through Objective Feature Scoring of Multiple Persons' Breathing Using Non-Contact RF Approach.

Sensors (Basel, Switzerland)·2023
Same author

Severe Carbamazepine Toxicity Treated with Continuous Venovenous Hemofiltration at Palestine Medical Complex: Two Case Reports.

International medical case reports journal·2022
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
Same journal

Predefined-time distributed optimal formation control for constrained UAV-UGV systems.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Feb 20, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.3K

Intelligent adaptive fractional order controller for mobile robot trajectory tracking.

Mohammad A Jaradat1, Khaled S Hatamleh2, Mohammad Hayajneh3

  • 1Mechanical Engineering Department, American University of Sharjah, Sharjah, United Arab Emirates; Mechanical Engineering Department, Jordan University of Science & Technology, Irbid, 22110, Jordan.

ISA Transactions
|February 18, 2026
PubMed
Summary
This summary is machine-generated.

An intelligent adaptive Fractional Order Full State Feedback Controller (FOFSC) improves differential drive robot trajectory tracking. This novel approach optimizes control gains for enhanced performance in autonomous delivery systems.

Keywords:
Differential Drive RobotFractional Order ControllerInteger Order ControllerIntelligent Adaptive Fractional Order Controller, Gray Wolf OptimizationTrajectory Tracking

More Related Videos

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.1K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.3K

Related Experiment Videos

Last Updated: Feb 20, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.3K
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.1K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.3K

Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence
  • Mechatronics

Background:

  • Autonomous wheeled mobile robots are crucial for tasks like delivery systems.
  • Precise trajectory tracking control is a key challenge for these robots.
  • Fractional-order control offers advantages over integer-order control due to memory and nonlocality.

Purpose of the Study:

  • To propose an intelligent adaptive Fractional Order Full State Feedback Controller (FOFSC) for enhanced differential drive robot (DDR) trajectory tracking.
  • To compare the performance of the proposed FOFSC with an Integer Order Full State Feedback Controller (IOFSC).
  • To evaluate adaptive and non-adaptive optimization approaches using Gray Wolf Optimization (GWO).

Main Methods:

  • Development of an FOFSC utilizing Gray Wolf Optimization (GWO) for gain tuning.
  • Implementation of both adaptive (online gain updates) and non-adaptive (offline gain tuning) optimization strategies.
  • Comparative analysis against an IOFSC using simulations and experimental validation on a QBot 2e robot platform.

Main Results:

  • The intelligent adaptive FOFSC demonstrated superior trajectory tracking performance compared to the IOFSC.
  • Key performance improvements include faster convergence speed and minimized tracking errors.
  • The adaptive FOFSC effectively handled disturbances and adapted to trajectory changes without re-tuning.

Conclusions:

  • The proposed intelligent adaptive FOFSC significantly enhances trajectory tracking for differential drive robots.
  • Fractional-order control, particularly in an adaptive configuration, offers a robust solution for autonomous systems.
  • The GWO algorithm effectively optimizes controller parameters for improved robotic navigation.