Kiarash AryankiaConcordia University Montreal · Department of Electrical and Computer Engineering
Kiarash Aryankia
PhD Candidate
About
10
Publications
2,490
Reads
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51
Citations
Citations since 2017
Introduction
I am working on Neural Network-based Formation Control of Second-order Multi-Agent Systems With Unknown Nonlinearities.
Education
September 2013 - September 2015
September 2008 - May 2012
Publications
Publications (10)
This paper is concerned with a new method for decomposing large scale systems into disjoint neighborhoods of subsystems with specific size determined a priori for managing communication load of a Jacobi based distributed optimal control method. The proposed decomposition method clusters subsystems into disjoint neighborhoods based on the strength o...
This paper proposes a distributed, false data injection (FDI) cyber-attack detection method in communication channels for a class of discrete-time, nonlinear, heterogeneous, multi-agent systems controlled by our formation-based controller. A distributed neural network (NN)-based observer is proposed that generates the residual signal which is used...
This paper considers a leader-following formation control problem for heterogeneous, second-order, uncertain, input-affine, nonlinear multi-agent systems modeled by a directed graph. A tunable, three-layer neural network (NN) is proposed with an input layer, two hidden layers, and an output layer to approximate an unknown nonlinearity. Unlike commo...
This paper proposes a distance-based formation control and target tracking for multi-agent systems where agents are modeled using second-order nonlinear systems in the presence of disturbance. By applying a rigid graph theory, we develop a neural network-based backstepping controller to address the distance-based formation control problem of nonlin...
This work establishes properties of the normalized rigidity matrix in two-and three-dimensional spaces. The upper bound of the normalized rigidity matrix singular values is derived for minimally and infinitesimally rigid frameworks in two-and three-dimensional spaces. We prove that the transformation of a framework does not affect the normalized ri...
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. A residual-based detection system, exploiting a neural network (NN)-based observer, is developed to detect false data injecti...
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. The radial basis function neural network (RBFNN) is used to overcome and compensate for the u...
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. The radial basis function neural network (RBFNN) is used to overcome and compensate for the u...
This paper proposes a neural network-based backstepping controller to address the distance-based formation control problem and target tracking for a class of nonlinear multiagent systems in Brunovsky form using rigid graph theory. The radial basis function neural network (RBFNN) is used to ensure the system stability in the presence of unknown nonl...
Questions
Question (1)
Consider you want to simulate any (stochastic) nonlinear dynamics with/without time delay in MATLAB scripts. The main question here is how to save the time of the events and write the triggering condition in MATLAB using the current and the triggered time (tk).
Projects
Projects (3)
Our purpose is mainly about backstepping control by running parallel sliding mode observer for a quadrotor Unmanned Ariel Vehicle. This sliding mode observer is filtered by a low pass filter to improve the performance of the observer. Since filtering sliding mode outputs eliminates stimulated discontinuity of the sign function of observer, smooth results achieved.
Our goal is concerned with a new method for decomposing large scale systems into disjoint neighborhoods of subsystems with specific size determined a priori for managing communication load of a Jacobi based distributed optimal control method.
