Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

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...

Controller Configurations

Controller Configurations

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...

PD Controller: Design

PD Controller: Design

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,...

Open and closed-loop control systems

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...

Feedback control systems

Feedback control systems

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...

Transfer Function in Control Systems

Transfer Function in Control Systems

The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...

You might also read

Related Articles

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

Sort by

Same author

Particle Filtering-Based In-Flight Icing Detection for Unmanned Aerial Vehicles.

Sensors (Basel, Switzerland)·2026

Same author

A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots.

Sensors (Basel, Switzerland)·2025

Same author

Developing a tablet-based brain-computer interface and robotic prototype for upper limb rehabilitation.

PeerJ. Computer science·2024

Same author

Adaptive-Robust Controller for Smart Exoskeleton Robot.

Sensors (Basel, Switzerland)·2024

Same author

Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation.

Sensors (Basel, Switzerland)·2023

Same author

A Novel Multi-Modal Teleoperation of a Humanoid Assistive Robot with Real-Time Motion Mimic.

Micromachines·2023

Search research articles

Related Experiment Video

Updated: Jan 9, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

Time-varying sliding mode control based finite-time prescribed performance function for robotic manipulators.

Sana Stihi¹, Raouf Fareh², Sofiane Khadraoui²

¹Research Institute of Sciences and Engineering (RISE), University of Sharjah, Sharjah, United Arab Emirates.

ISA Transactions

|November 30, 2025

Summary

This summary is machine-generated.

This study introduces a novel Time-Varying Sliding-Mode Controller (TVSMC) that eliminates reaching phases and ensures finite-time error convergence for robotic manipulators. The new approach enhances robustness and reduces chattering for precise control.

Keywords:

Finite-time prescribed performance function Power rate reaching law Robot manipulator Stability analysis Time varying sliding surface Tracking control

More Related Videos

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

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

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

Published on: March 10, 2011

Related Experiment Videos

Last Updated: Jan 9, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

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

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

Published on: March 10, 2011

Area of Science:

Robotics
Control Systems Engineering
Applied Mathematics

Background:

Sliding Mode Control (SMC) offers robustness for robot manipulators but suffers from chattering and long reaching phases.
Traditional Time-Varying Sliding Mode Surfaces (TVSMS) can be sensitive to initial conditions and parameter selection, limiting finite-time convergence.
Achieving robustness and finite-time convergence from any initial state remains a significant challenge in robotic control.

Purpose of the Study:

To develop a novel Time-Varying Sliding-Mode Controller (TVSMC) that integrates a Finite-Time Prescribed Performance Function (FTPPF).
To eliminate the reaching phase and ensure finite-time error convergence for robot manipulators.
To enhance robustness against uncertainties and disturbances while mitigating chattering.

Main Methods:

Integration of a Finite-Time Prescribed Performance Function (FTPPF) into a Time-Varying Sliding Mode Surface (TVSMS) design.
Development of a novel TVSMS based on FTPPF to ensure error convergence within a predetermined time frame.
Utilizing the Lyapunov theorem for finite-time stability analysis and experimental validation on a MICO 4-DOF robot.

Main Results:

The proposed TVSMS ensures finite-time error convergence, eliminates the reaching phase, and reduces sensitivity to initial conditions.
The controller effectively mitigates the chattering problem associated with SMC and enhances robustness during the reaching phase.
Experimental results demonstrate superior performance, robustness, and resilience to disturbances compared to conventional methods.

Conclusions:

The novel TVSMC with FTPPF offers a simplified yet highly robust solution for high-precision robotic applications.
The approach guarantees finite-time convergence and improved transient response shaping with minimal parameter tuning.
This controller presents a promising advancement for precise and reliable robotic manipulation under uncertainty.