Bogotá, Colombia
Zouari, Farouk
Boulkroune, Abdesselem
Ibeas, Asier
2020-04-29T19:43:39Z
2020-04-29T19:43:39Z
2017
http://dx.doi.org/10.1016/j.neucom.2016.11.036
http://hdl.handle.net/20.500.12010/9077
research is concerned with the problem of generalized function projective
synchronization of nonlinear uncertain time-delay incommensurate fractional-order
chaotic systems with input nonlinearities. The considered problem is challenging
owing to the presence of unmeasured master-slave system states, external dynamical
disturbances, unknown nonlinear system functions, unknown time-varying delays,
quantized outputs, unknown control direction, unknown actuator nonlinearities
(backlash-like hysteresis, dead-zone and asymmetric saturation actuators) and distinct
fractional-orders. Under some mild assumptions and using aputo’s definitions for
fractional-order integrals and derivatives, the design procedure of the proposed neural
adaptive controller consists of a number of steps to solve the generalized function
projective synchronization problem. First, smooth functions and the mean value
theorem are utilized to overcome the difficulties from actuator nonlinearities and
distributed time-varying delays, respectively. Then, a simple linear observer is
established to estimate the unknown synchronization error variables. In addition, a
Nussbaum function is incorporated to cope with the unknown control direction and a
neural network is adopted to tackle the unknown nonlinear functions. The
combination of the frequency distributed model, the Razumikhin Lemma, the neural
network parameterization, the Lyapunov method and the arbalat’s le a is
employed to perform the stability proof of the closed-loop system and to derive the
adaption laws. The major advantages of this research are that: (1) the Strictly Positive
Real (SPR) condition on the estimation error dynamics is not required, (2) the considered class of master-slave systems is relatively large, (3) all signals in the
resulting closed-loop systems are semi-globally uniformly ultimately bounded and the
synchronization errors semi-globally converge to zero. Finally, numerical examples
are presented to illustrate the performance of the proposed synchronization scheme.
72 páginas
image/jepg
Universidad de Bogotá Jorge Tadeo Lozano
Generalized function projective synchronization
Uncertain time-delay chaotic systems
Incommensurate fractional-order systems
Input nonlinearities
Razumikhin Lemma
Frequency distributed model
Adaptive quantized output-feedback control
Neural Adaptive quantized output-feedback control- based synchronization of uncertain time-delay incommensurate fractionalorder chaotic systems with input nonlinearities
Artículo
Caos determinista
Sistemas no lineales
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/acceptedVersion
Abierto (Texto Completo)
http://dx.doi.org/10.1016/j.neucom.2016.11.036
instname:Universidad de Bogotá Jorge Tadeo Lozano
reponame:Repositorio Institucional de la Universidad de Bogotá Jorge Tadeo Lozano
info:eu-repo/semantics/article