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

Second Order systems II01:18

Second Order systems II

79
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
79
Control System Problem01:21

Control System Problem

95
In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
95
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

78
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...
78
Feedback control systems01:26

Feedback control systems

268
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...
268
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

84
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....
84
First Order Systems01:21

First Order Systems

81
First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
81

You might also read

Related Articles

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

Sort by
Same author

Structural characterization, controlled enzymatic hydrolysis and immunomodulatory activities of three ginseng polysaccharides.

Carbohydrate research·2026
Same author

Phase 1 randomized trial of HS-10353, a novel GABA(A) positive allosteric modulator for treatment of major depressive disorder.

BMC medicine·2026
Same author

Pharmacokinetics, dosing exposure and safety of oral ibuprofen in Chinese preterm neonates with patent ductus arteriosus: preliminary report.

BMJ paediatrics open·2026
Same author

Regulation of bubble evolution dynamics by surfactants during water electrolysis.

Journal of colloid and interface science·2026
Same author

Population Pharmacokinetics of Sacubitril/Valsartan in Patients with Heart Failure and End-Stage Renal Disease Undergoing Peritoneal Dialysis.

Clinical pharmacokinetics·2026
Same author

Silencing SFRP1 in bone mesenchymal stem cells alleviates pediatric B-ALL-driven bone loss by activating Wnt/β-catenin signaling.

Journal of orthopaedic translation·2026

Related Experiment Video

Updated: May 25, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.5K

Switching dynamic event-triggered disturbance rejection control for uncertain Lipschitz nonlinear system using

Guanghao Su1, Zhenlei Wang2

  • 1Key Laboratory of Smart Manufacturing in Energy Chemical Process (Ministry of Education), East China University of Science and Technology, Shanghai 200237, China.

ISA Transactions
|February 27, 2025
PubMed
Summary

This study introduces an event-triggered control method for nonlinear systems facing disturbances. The approach enhances disturbance rejection and reduces control signal frequency, improving system performance.

Keywords:
Disturbance reconstructionEvent-triggered controlLipschitz nonlinear systemsMultiple intermediate estimatorsState estimation

More Related Videos

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K

Related Experiment Videos

Last Updated: May 25, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.5K
WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K

Area of Science:

  • Control Systems Engineering
  • Nonlinear Dynamics
  • Applied Mathematics

Background:

  • Uncertainty and time-varying disturbances challenge the stability and performance of nonlinear systems.
  • Traditional continuous control methods can be communication-intensive and computationally expensive.

Purpose of the Study:

  • To develop an event-triggered disturbance rejection control strategy for uncertain Lipschitz nonlinear systems.
  • To design a controller that minimizes communication and computation while ensuring system stability and performance.
  • To guarantee a minimum inter-event time for practical implementation.

Main Methods:

  • Design of a joint state and disturbance observer using transformed intermediate variables.
  • Recursive observer construction to estimate system states and disturbances.
  • Development of an event-triggered controller with a dynamic trigger variable and a mandatory resting interval.
  • Incorporation of a guaranteed minimum inter-event time mechanism.

Main Results:

  • The proposed event-triggered control method effectively rejects time-varying disturbances in uncertain Lipschitz nonlinear systems.
  • Numerical simulations demonstrate a 59.6% reduction in steady-state error.
  • The minimum trigger interval was extended by at least 2.44 times compared to existing methods, reducing control signal frequency.

Conclusions:

  • The developed event-triggered control strategy offers significant performance improvements for nonlinear systems with disturbances.
  • The method provides a practical approach to reduce control updates while maintaining system stability and accuracy.
  • This research contributes to efficient and robust control design for complex dynamic systems.