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Control Systems01:10

Control Systems

1.1K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.1K
Feedback control systems01:26

Feedback control systems

304
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...
304
Effects of feedback01:24

Effects of feedback

548
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
548
Pole and System Stability01:24

Pole and System Stability

277
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
277
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

482
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...
482
Open and closed-loop control systems01:17

Open and closed-loop control systems

714
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...
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Related Experiment Video

Updated: Jun 23, 2025

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

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Robust Output Feedback Stabilization and Tracking for an Uncertain Nonholonomic Systems with Application to a Mobile

Muhammad Junaid Rabbani1, Attaullah Y Memon2, Muhammad Farhan3

  • 1Department of Electrical Engineering, National University of Computer and Emerging Sciences, Karachi 75030, Pakistan.

Sensors (Basel, Switzerland)
|June 19, 2024
PubMed
Summary

This study introduces robust output feedback control for underactuated nonholonomic systems, enhancing stabilization and trajectory tracking despite uncertainties. The novel approach combines backstepping and sliding mode control (SMC) with a high gain observer (HGO).

Keywords:
backstepping controlhigh gain observernonholonomic wheeled mobile robotsliding mode controlstabilizationtrajectory tracking

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Area of Science:

  • Control Systems Engineering
  • Robotics
  • Nonholonomic Dynamics

Background:

  • Underactuated nonholonomic systems present significant control challenges due to limited actuators and velocity constraints.
  • Existing control methods often struggle with model uncertainties, external disturbances, and the absence of full state information.

Purpose of the Study:

  • To develop a robust output feedback control strategy for simultaneous stabilization and trajectory tracking.
  • To address challenges including nontriangular normal forms, non-affine internal dynamics, and non-minimum phase zero dynamics.
  • To overcome limitations posed by model uncertainties, external disturbances, and lack of velocity measurements.

Main Methods:

  • Input-output feedback linearization and coordinate transformation to achieve a generalized normal form.
  • Integration of backstepping and sliding mode control (SMC) techniques.
  • Development of a full-order high gain observer (HGO) for state and derivative estimation.

Main Results:

  • A novel robust output feedback controller is synthesized by combining HGO and backstepping SMC.
  • The proposed controller demonstrates effective stabilization and trajectory tracking for underactuated nonholonomic systems.
  • Simulation results validate the controller's robustness against bounded uncertainties, using a differential-drive mobile robot as a case study.

Conclusions:

  • The combined backstepping SMC and HGO approach provides a robust solution for controlling complex underactuated nonholonomic systems.
  • This method effectively handles system uncertainties and disturbances without requiring velocity measurements.
  • The proposed control scheme offers a promising direction for advanced robotics and autonomous systems.