Related Experiment Videos
Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings
IEEE Transactions on Cybernetics
|August 16, 2012
Summary
This study achieves distributed synchronization in agent networks with random controllers and nonlinearities using Lyapunov functions. The findings reveal impacts of coupling strength and probabilities on convergence speed.
Area of Science:
- Control Systems Engineering
- Networked Systems
- Stochastic Processes
Background:
- Investigates distributed synchronization in networks of agent systems.
- Addresses challenges posed by controllers, nonlinearities, and Bernoulli switchings.
Purpose of the Study:
- To achieve distributed synchronization in agent networks with randomly occurring nonlinearities, controllers, and updating laws.
- To analyze the impact of system parameters on synchronization performance.
Main Methods:
- Utilizes Lyapunov functions to establish synchronization criteria.
- Employs semi-definite programming for solving derived conditions.
- Introduces Bernoulli stochastic variables to model random occurrences.
Main Results:
- Distributed synchronization in mean square is achievable under specific criteria.
- Coupling strength, Bernoulli probabilities, and nonlinearities significantly affect convergence speed and control strength.
- Distributed adaptive controllers demonstrate advantages over conventional ones.
Conclusions:
- The proposed method ensures reliable distributed synchronization in complex agent networks.
- The findings provide insights into optimizing network control and synchronization.
- The study validates theoretical results with numerical simulations.
Related Concept Videos
01:27State Space Representation
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
01:24BIBO stability of continuous and discrete -time systems
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
01:25Multimachine Stability
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
01:23Linear time-invariant Systems
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
01:21Distributed Loads: Problem Solving
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
01:25Distribution Reliability and Automation
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...