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Mohammad Haeri

Researcher at Sharif University of Technology

Publications -  280
Citations -  5469

Mohammad Haeri is an academic researcher from Sharif University of Technology. The author has contributed to research in topics: Control theory & Model predictive control. The author has an hindex of 33, co-authored 270 publications receiving 4852 citations. Previous affiliations of Mohammad Haeri include University of Saskatchewan & Islamic Azad University, Science and Research Branch, Tehran.

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A necessary condition for double scroll attractor existence in fractional-order systems

TL;DR: Based on the stability theorem in fractional differential equations, a necessary condition is given to check existence of double scroll attractor in a fractional-order system as mentioned in this paper, and numerical simulations are presented to evaluate accuracy of this condition.
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Chaotic attractors in incommensurate fractional order systems

TL;DR: In this paper, a necessary condition is given to check the existence of 1-scroll, 2-scroll or multi-scroll chaotic attractors in a fractional order system, based on the stability theorems in fractional differential equations.
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A note on the stability of fractional order systems

TL;DR: A new approach is suggested to investigate stability in a family of fractional order linear time invariant systems with order between 1 and 2, which relies on finding a linear ordinary system that possesses the same stability property as the fractional orders.
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Synchronization of chaotic fractional-order systems via active sliding mode controller

TL;DR: In this article, a controller based on active sliding mode theory is proposed to synchronize chaotic fractional-order systems in master-slave structure, where master and slave systems may be identical or different.
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Comparison of different one-dimensional maps as chaotic search pattern in chaos optimization algorithms

TL;DR: This paper proposes and compares different one-dimensional maps as chaotic search patterns in the constraint nonlinear optimization problems and applies them in specific optimization algorithm (weighted gradient direction based chaos optimization algorithm) and compares them based on numerical simulation results.