فصلنامه هوش محاسباتی در مهندسی برق
سال سوم شماره 1 (بهار 1391)

Phasor measurement units (PMUS) are crucial elements of wide-area state estimation system in Smart Grids, as they maintain a high quality observability on electrical quantities of power system. This paper proposes a new approach for multi-objective PMU placement considering actual worth of contingency conditions. Moreover, a new fitness function is introduced to simultaneously find the minimum number of PMUs as well as to maximize the measurement redundancies. In addition, a cellular learning automata based algoritm is employed for optimization process. The developed method is applied to IEEE test systems and obtained results are reported in several scenarios. Detailed numerical results and comparisons presented in the paper show that the proposed approach could noticeably improve the quality of problem solutions under uncertainties and can be used as an effective tool for multi-objective PMU placement within an actual large-scale transmission network.

In this paper we consider the problem of blood vessel segmentation in retinal images. After enhancing the retinal image we use green channel of images for segmentation as it provides better discrimination between vessels and background. We consider the negative of retinal green channel image as a topographical surface and extract ridge points on this surface. The points with this property are located on the centerline of vessels. In presence of noise and non-uniform illumination the extracted ridge points appear as separated points which consist parts of vessel centerline. In order to connect separated ridge points and extending them for thin vessel extraction, we introduce a bank of directional filters to determine proper direction for extending the ridge end points. The ridge end points grow to provide link between separated parts of centerline using the introduced procedure. The result of experiment on images in the DRIVE database shows the proposed method outperforms the existing methods. Performance of the proposed method was evaluated based on accuracy, false positive and false negative criteria.

This paper presents experimental results of the V/f speed control for an induction motor under different operating conditions such as step changes in reference speed and the load torque. Genetic PI-based and Fuzzy-Logic-based controllers are considered. Then, the performances of these controllers are experimentally compared with each other under these different operating conditions.

Today, many widely used image processing algorithms based on human visual system have been developed. In this paper a smart edge detection based on modeling the performance of simple and complex cells and also modeling and multi-scale image processing in the primary visual cortex is presented. A way to adjust the parameters of Gabor filters (mathematical models of simple cells) And the proposed non-linear threshold response are presented in order to Modeling of simple and complex cells. Also, due to multi-scale modeling analysis conducted in the human retina, in the proposed algorithm, all edges of the small and large structures with high precision are detected and localized. Comparing the results of the proposed method for a reliable database with conventional methods shows the higher Performance (about 4-13%) and reliability of the proposed method in the detection and localization of edge.

An Observer in the supervisory control observes responses of a discrete system to events of its environment and reports an unsafe/ critical situation if the response is undesired. An undesired response from the system indicates the system response does not adhere to users’ requirements of the system. Therefore, events and conditions of the system environment and user’s requirements of the system are basic elements to observer in determining correctness of the system response. However, the noteworthy matter is that the events, conditions, and requirements should be defined based on data of problem domain because discrete data are primary ingredients of the environment in discrete systems and they are used by system users as a gauge to express their requirements playing a vital role in safety-critical systems, such as medical and avionic ones. A large quantity of methods has already been proposed to model and simulate supervisory control of discrete systems however, a systematic method relying on data of problem domain is missing. Having extracted events, conditions, and user’s requirements from data of problem domain, a Petri-Net automaton is constructed for identifying violation of user’s requirements. The net constitutes the core of the observer and it is used to identify undesired responses of the system. In the third step, run-time simulation of the observer is suggested using multithreading mechanism and Task Parallel Library (TPL) technology of Microsoft. Finally, a case study of a discrete concurrent system is proposed, the method applied and simulation results are analyzed based on the system implementation on a multi-core computer.

This paper presents an intelligent optimal design control strategy for current and voltage of boost DC-DC convertors in fuel cell power systems by considering detailed model for different operating points. The proposed control strategy is designed based on a state feedback whereas the controllability and the stability region are analyzed. Moreover, in order to determine of the optimal coefficients of state feedback and zero steady state error in voltage signal, in the core of the proposed control method a heuristic algorithm namely Particle Swarm Optimization (PSO) is utilized. The results are presented in the different load conditions. In order to show the feasibility of the proposed control strategy, the controller is implemented both average model and detailed model of convertor and the results are compared.