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Delay dependent complex-valued bidirectional associative memory neural networks with stochastic and impulsive effects: An exponential stability approach

Chinnamuniyandi Maharajan, Chandran Sowmiya, Changjin Xu (2024)

Kybernetika

This paper investigates the stability in an exponential sense of complex-valued Bidirectional Associative Memory (BAM) neural networks with time delays under the stochastic and impulsive effects. By utilizing the contracting mapping theorem, the existence and uniqueness of the equilibrium point for the proposed complex-valued neural networks are verified. Moreover, based on the Lyapunov - Krasovskii functional construction, matrix inequality techniques and stability theory, some novel time-delayed...

Design of a multivariable neural controller for control of a nonlinear MIMO plant

Stanisław Bańka, Paweł Dworak, Krzysztof Jaroszewski (2014)

International Journal of Applied Mathematics and Computer Science

The paper presents the training problem of a set of neural nets to obtain a (gain-scheduling, adaptive) multivariable neural controller for control of a nonlinear MIMO dynamic process represented by a mathematical model of Low-Frequency (LF) motions of a drillship over the drilling point at the sea bottom. The designed neural controller contains a set of neural nets that determine values of its parameters chosen on the basis of two measured auxiliary signals. These are the ship's current forward...

Drive network to a desired orbit by pinning control

Quanjun Wu, Hua Zhang (2015)

Kybernetika

The primary objective of the present paper is to develop an approach for analyzing pinning synchronization stability in a complex delayed dynamical network with directed coupling. Some simple yet generic criteria for pinning such coupled network are derived analytically. Compared with some existing works, the primary contribution is that the synchronization manifold could be chosen as a weighted average of all the nodes states in the network for the sake of practical control tactics, which displays...

Dynamic external force feedback loop control of a robot manipulator using a neural compensator - Application to the trajectory following in an unknown environment

Farid Ferguene, Redouane Toumi (2009)

International Journal of Applied Mathematics and Computer Science

Force/position control strategies provide an effective framework to deal with tasks involving interaction with the environment. One of these strategies proposed in the literature is external force feedback loop control. It fully employs the available sensor measurements by operating the control action in a full dimensional space without using selection matrices. The performance of this control strategy is affected by uncertainties in both the robot dynamic model and environment stiffness. The purpose...

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