COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)
Year:2012 | Volume:3 | Issue:1 (6)|Papers Count:6

Phasor measurement units (PMUS) are crucial elements of wide-area state estimation system in Smart Grids, as they maintain a high quality of 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 algorithm 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 the 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 the 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 that the proposed method outperforms the existing methods. The 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.

Attention to the human visual system and simulating it in developing new image processing algorithms has attracted researchers attention. In this paper an intelligent edge detection method based on modeling of simple and complex cells fuzzy modeling of multi-scale analysis of images in primary visual cortex is presented. For effective modeling of simple and complex cells response on edge detection, a method is proposed to adjust the parameters of Gabor filter (as a mathematical model of simple cells) and the nonlinear function as a thresholding function. The Main advantage of the proposed method in comparison with other common methods of edge detection is that the proposed fuzzy model for multi-scale analysis does not receive any parameters as its input. And because of modeling the multi-scale analysis in the human retina, in the proposed method, all edges of the fine and coarse structures in the image will be detected and resolved with high accuracy. For better comparison, the best results of the Canny method on bank of valid data are produced by genetic algorithm and compared with proposed method results. Simulations show an increment of 4% to 13% in the performance measure for the proposed method. Visual comparison also shows a better performance of the proposed method in detecting and resolving edges.

In the supervisory control of systems, an observer monitors discrete system responses to the events of the system environment and will report an unsafe or critical situation if the response is undesired. The undesired response means that it does not adhere to user’s requirements. Several methods have already been proposed to model and simulate supervisory control of discrete systems; however, there is a lack of a systematic method relying on problem domain data. To present a domain-based method, we use a three-step method. In the first step, we commence with discrete data. Discrete data are primary ingredients of the discrete systems environment and 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. We use the discrete data for definition of events and conditions constituting requirements definition. Having extracted events, conditions, and user’s requirements from problem domain data, a Petri-Net automaton is constructed for identifying violation of user’s requirements in the second step. 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, by proposing the Train Protection System as a case study of a discrete concurrent system, we tangibly show how one can apply the steps of our method for modeling and simulation of the observer. The simulation results were analyzed based on the system implementation on a multi-core computer.

This paper presents an intelligent optimal design control strategy for the current and voltage of boost DC-DC convertors in fuel cell power systems by considering the 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 for different load conditions. In order to show the feasibility of the proposed control strategy, the controller is implemented by both average model and detailed model of convertor and the results are compared.