Faridoon Shabaninia

Learn More
This paper proposes a controller design for urban traffic networks. The growing demand for faster transportation has led to heavy congestion in road traffic networks, necessitating the need for traffic-responsive intelligent signal control systems. The developed signal control system based on uncertain information of the environment must be capable of(More)
Availability of data from Phasor Measurement Units (PMUs), characterized by their high accuracy to measure node voltage phasors, allows a simplification of the State Estimation (SE) problems. In this paper Iterated Kaiman Filter (IKF) algorithm, as a new method, has been used for SE of a test Active Distributed Network (ADN) integrating PMU measurements. In(More)
The main contribution of this paper is to design a more accurate optimal/suboptimal fault tolerant state estimator. Federated filters compose of a set of local filters and a master filter, the local filters work in parallel and their solutions are periodically fused by the master filter yielding a global solution. Federated ensemble Kalman filter no reset(More)
Function approximation is a widely used method in system identification and recently RBF networks have been proposed as powerful tools for that. Existing algorithms suffer from some restrictions such as slow convergence and/or encountering to bias in parameter convergence. This paper is an attempt to improve the above problems by proposing new methods of(More)
This paper describes the Neuro-Fuzzy logic based controller design for the buck DC-DC converters. As it is obvious form the previous type of controllers (conventional PID) for such converters which have been designed under the worst case condition for high load and lowest line condition, they present a lower loop in band width, and the system response is(More)
In this paper, a distributed ensemble Kalman filter (DEnKF) is proposed for sensor fusion in a sensor network. To solve data fusion problem in distributed sensor network, consensus filter is implemented. To estimates nodes' states, each node uses local and neighbors' information rather than the information from all nodes in the network. So, due to this(More)