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

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

74
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...
74
Root-Locus Method01:19

Root-Locus Method

116
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
116
PD Controller: Design01:26

PD Controller: Design

153
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,...
153
PI Controller: Design01:24

PI Controller: Design

151
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...
151
PID Controller01:19

PID Controller

84
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...
84
Controller Configurations01:22

Controller Configurations

73
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...
73

You might also read

Related Articles

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

Sort by
Same author

Real-World Multicenter Study on the Effectiveness of Dolutegravir Plus Lamivudine in Treatment-Naive People Living with HIV with Baseline HIV-1 RNA > 500,000 Copies/mL.

Infectious diseases and therapy·2026
Same author

Cross-Condition Tool Wear State Monitoring via Multi-Source Sensor Signal Fusion and Supervised Transfer Learning.

Sensors (Basel, Switzerland)·2026
Same author

End-to-end multi-domain joint coding framework for 3D light field video based on viewpoint-disparity representation.

Optics express·2026
Same author

Associations of High Serum Ferritin Concentrations with Learning Disability and Attention Deficit/Hyperactivity Disorder among Children and Adolescents.

Journal of the Academy of Nutrition and Dietetics·2026
Same author

A MWCNT-PVDF/PCL Piezo-Triboelectric Coupled Nanogenerator by Synergistic Regulation of Microcrystalline Phase and Patterned Structure for Self-Powered Sensors.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Research on an Underwater Visual Enhancement Method Based on Adaptive Parameter Optimization in a Multi-Operator Framework.

Sensors (Basel, Switzerland)·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 14, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.5K

Research on Trajectory Tracking Control Method for Crawler Robot Based on Improved PSO Sliding Mode Disturbance

Zhiyong Yang1,2,3, Qing Lang3, Yuhong Xiong3

  • 1Engineering Research and Design Institute of Agricultural Equipment, Hubei University of Technology, Wuhan 430068, China.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an improved particle swarm optimization and sliding mode active disturbance rejection control (SPSO-SMADRC) for crawler robots. The SPSO-SMADRC method significantly enhances trajectory tracking accuracy and robustness in uneven terrains.

Keywords:
crawler robotpath vector field guidancesliding mode active disturbance rejection controltrajectory tracking

More Related Videos

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.6K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.6K

Related Experiment Videos

Last Updated: May 14, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.5K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.6K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.6K

Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence and Optimization
  • Autonomous Navigation

Background:

  • Crawler robots face challenges in trajectory tracking accuracy and parameter tuning, especially in uneven terrains.
  • Disturbances from terrain undulations and soil inhomogeneity significantly impact robot trajectory deviation.
  • Existing methods like standard sliding mode active disturbance rejection control (SMADRC) can struggle with parameter optimization and local optima.

Purpose of the Study:

  • To develop an advanced trajectory tracking control method for crawler robots operating in challenging environments.
  • To improve the global search capability of particle swarm optimization (PSO) for controller parameter tuning.
  • To enhance the navigation accuracy and robustness of crawler robots through an improved control strategy.

Main Methods:

  • Established kinematic and dynamic models for crawler robots, incorporating terrain disturbance factors.
  • Employed a vector field guidance approach to convert trajectory tracking into a heading control problem.
  • Designed a nonlinear extended state observer for disturbance estimation and a velocity-based SMADRC controller for real-time motion regulation.
  • Introduced a nonlinear dynamic adjustment strategy for inertia weight and learning factors in PSO to improve global search capability (SPSO-SMADRC).

Main Results:

  • The SPSO-SMADRC method achieved significantly reduced position and heading angle errors compared to conventional methods on U-shaped and V-shaped trajectories.
  • Maximum position errors were as low as 8.28 cm and 9.26 cm, with average errors of 1.41 cm and 2.94 cm.
  • Navigation tracking accuracy was improved, with reductions in maximum position error by up to 38.21% and average position error by up to 65.53%.

Conclusions:

  • The proposed SPSO-SMADRC method offers superior trajectory tracking performance and enhanced system robustness for crawler robots.
  • This advanced control strategy provides effective support for high-precision autonomous navigation in complex, unstructured terrains.
  • The improved PSO algorithm overcomes limitations of standard PSO, leading to more effective controller parameter tuning.