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Found 6 papers, 0 papers with code
Cyberattack Detection for Nonlinear Leader-Following Multi-Agent Systems Using Set-Membership Fuzzy Filtering
A distributed cyberattack detection method, based on a new fuzzy set-membership filtering method, which consists of two steps, namely a prediction step and a measurement update step, is developed for each agent to identify two types of cyberattacks at the time of their occurrence.
Formation Control of Nonlinear Multi-Agent Systems Using Three-Layer Neural Networks
The NN-based term compensates for the unknown nonlinearity in the dynamics of multi-agent systems, and semi-global asymptotic tracking results are rigorously proven using the Lyapunov stability theory.
Cyber-Attack Detection in Discrete Nonlinear Multi-Agent Systems Using Neural Networks
This paper proposes a distributed cyber-attack detection method in communication channels for a class of discrete, nonlinear, heterogeneous, multi-agent systems that are controlled by our proposed formation-based controller.
Neuro-Adaptive Formation Control and Target Tracking for Nonlinear Multi-Agent Systems with Time-Delay
This paper proposes an adaptive neural network-based backstepping controller that uses rigid graph theory to address the distance-based formation control problem and target tracking for nonlinear multi-agent systems with bounded time-delay and disturbance.
Classifying Unordered Feature Sets with Convolutional Deep Averaging Networks
Unordered feature sets are a nonstandard data structure that traditional neural networks are incapable of addressing in a principled manner.
On the Definiteness of Earth Mover's Distance and Its Relation to Set Intersection
Positive definite kernels are an important tool in machine learning that enable efficient solutions to otherwise difficult or intractable problems by implicitly linearizing the problem geometry.
