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Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

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...

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...

One-Degree-of-Freedom System

One-Degree-of-Freedom System

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...

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,...

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Related Experiment Video

Updated: Mar 29, 2026

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

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

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

Qikun Shen, Peng Shi, Yan Shi

IEEE Transactions on Cybernetics

|November 24, 2015

Summary

This study develops distributed adaptive fuzzy control for uncertain nonlinear multiagent systems. Controllers ensure follower agents synchronize with a leader, even with limited state information, using novel observers and fuzzy logic systems.

Related Experiment Videos

Last Updated: Mar 29, 2026

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

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

Area of Science:

Control Systems Engineering
Artificial Intelligence
Networked Systems

Background:

Multiagent systems (MAS) often face uncertainties and require distributed control.
Fixed topology directed graphs are common in MAS but pose control challenges.
Limited output information complicates controller design in decentralized systems.

Purpose of the Study:

To investigate distributed adaptive fuzzy control for high-order uncertain nonlinear multiagent systems.
To design controllers using only local output information from followers and neighbors.
To achieve asymptotic synchronization of followers to a leader agent.

Main Methods:

Utilized fuzzy logic systems (FLS) for approximating unknown nonlinear functions.
Developed equivalent output injection sliding mode observers (SMO) for state estimation.
Employed Lyapunov functions and algebraic graph theory for stability analysis within the Filippov framework.

Main Results:

Achieved semi-globally uniformly ultimate bounded tracking errors for follower agents.
Demonstrated successful state estimation using observer-based controllers.
Validated the proposed control design through numerical simulations.

Conclusions:

The developed observer-based distributed adaptive fuzzy control is effective for uncertain nonlinear multiagent systems.
The approach successfully handles limited output information and ensures leader-following synchronization.
The techniques offer a robust solution for complex networked control problems.