[HTML][HTML] Composite learning sliding mode synchronization of chaotic fractional-order neural networks
Z Han, S Li, H Liu - Journal of Advanced Research, 2020 - Elsevier
In this work, a sliding mode control (SMC) method and a composite learning SMC (CLSMC)
method are proposed to solve the synchronization problem of chaotic fractional-order neural …
method are proposed to solve the synchronization problem of chaotic fractional-order neural …
A new RBF neural network-based fault-tolerant active control for fractional time-delayed systems
Recently, intelligent control techniques have received considerable attention. In most
studies, the systems' model is assumed to be without any delay, and the effects of faults and …
studies, the systems' model is assumed to be without any delay, and the effects of faults and …
Nonlinear observer with reduced sensors for WECS involving Vienna rectifiers—Theoretical design and experimental evaluation
This paper presents a novel sensorless high-gain observer for wind energy conversion
systems (WECS) incorporating Vienna rectifiers. Vienna rectifiers offer several advantages …
systems (WECS) incorporating Vienna rectifiers. Vienna rectifiers offer several advantages …
Leader-follower formation of light-weight UAVs with novel active disturbance rejection control
Considering that the formation composed of light-weight UAVs is highly susceptible to the
interference, which may from the changes in the external environment and the uncertainty of …
interference, which may from the changes in the external environment and the uncertainty of …
Recurrent neural network-based robust nonsingular sliding mode control with input saturation for a non-holonomic spherical robot
SB Chen, A Beigi, A Yousefpour, F Rajaee… - IEEE …, 2020 - ieeexplore.ieee.org
We develop a new robust control scheme for a non-holonomic spherical robot. To this end,
the mathematical model of a pendulum driven non-holonomic spherical robot is first …
the mathematical model of a pendulum driven non-holonomic spherical robot is first …
On the dynamical investigation and synchronization of variable-order fractional neural networks: The Hopfield-like neural network model
H Jahanshahi, E Zambrano-Serrano, S Bekiros… - The European Physical …, 2022 - Springer
Since the variable-order fractional systems show more complex characteristics and more
degrees of freedom due to time-varying fractional derivatives, we introduce a variable-order …
degrees of freedom due to time-varying fractional derivatives, we introduce a variable-order …
Synchronization of fractional time-delayed financial system using a novel type-2 fuzzy active control method
In the present article, as a new approach, a fuzzy disturbance observer is combined with an
active controller for the synchronization of fractional-order time-delayed systems. Since the …
active controller for the synchronization of fractional-order time-delayed systems. Since the …
Hopf bifurcation and synchronization of a five-dimensional self-exciting homopolar disc dynamo using a new fuzzy disturbance-observer-based terminal sliding mode …
Z Wei, A Yousefpour, H Jahanshahi… - Journal of the Franklin …, 2021 - Elsevier
Having found hidden hyperchaos in a 5D self-exciting homopolar disc dynamo, we study the
existence of a Hopf bifurcation, which leads to unstable limit cycles bifurcating from a stable …
existence of a Hopf bifurcation, which leads to unstable limit cycles bifurcating from a stable …
Control of a symmetric chaotic supply chain system using a new fixed-time super-twisting sliding mode technique subject to control input limitations
Control of supply chains with chaotic dynamics is an important, yet daunting challenge
because of the limitations and constraints there are in the amplitude of control efforts. In real …
because of the limitations and constraints there are in the amplitude of control efforts. In real …
Memory-augmented system identification with finite-time convergence
A Vahidi-Moghaddam, M Mazouchi… - IEEE Control Systems …, 2020 - ieeexplore.ieee.org
This letter presents a memory-augmented system identifier with finite-time convergence for
continuous-time uncertain nonlinear systems. A memory of events with significant effect on …
continuous-time uncertain nonlinear systems. A memory of events with significant effect on …