H
Heidar Ali Talebi
Researcher at Amirkabir University of Technology
Publications - 308
Citations - 4980
Heidar Ali Talebi is an academic researcher from Amirkabir University of Technology. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 32, co-authored 303 publications receiving 4026 citations. Previous affiliations of Heidar Ali Talebi include Concordia University & University of Western Ontario.
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Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system
TL;DR: In this paper, a hybrid wind-solar generation microgrid system with hydrogen energy storage is designed for a 20-year period of operation using novel multi-objective optimization algorithm to minimize the three objective functions namely annualized cost of the system, loss of load expected and loss of energy expected.
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A stable neural network-based observer with application to flexible-joint manipulators
TL;DR: A stable neural network (NN)-based observer for general multivariable nonlinear systems is presented in this paper and the stability of the recurrent neural network observer is shown by Lyapunov's direct method.
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A Recurrent Neural-Network-Based Sensor and Actuator Fault Detection and Isolation for Nonlinear Systems With Application to the Satellite's Attitude Control Subsystem
TL;DR: A robust fault detection and isolation (FDI) scheme for a general class of nonlinear systems using a neural-network-based observer strategy and requires no restrictive assumptions on the system and/or the FDI algorithm.
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A Decentralized Power Management and Sliding Mode Control Strategy for Hybrid AC/DC Microgrids including Renewable Energy Resources
TL;DR: In this paper, a new decentralized robust strategy to improve small and large-signal stability and power sharing of hybrid AC/DC microgrids and improve its performance for nonlinear and unbalanced loads is presented.
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Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems
TL;DR: By utilizing the proposed methodology, isolation of simultaneous occurring faults can also be handled and the extended LMI characterization is used to reduce the conservativeness of the solution by eliminating the couplings between the Lyapunov matrices and the agents' matrices.