International Journal of Smart Electrical Engineering
Volume:7 Issue: 1, Winter 2018

Supervisory control and fault diagnosis of hybrid systems need to have complete information about the discrete states transitions of the underling system. From this point of view, the hybrid system should be abstracted to a Discrete Trace Transition System (DTTS) and represented by a discrete mode transition graph. In this paper an effective method is proposed for generating discrete mode transition graph of a hybrid system. This method can be used for a general class of industrial hybrid plants which are defined by Polyhedral Invariant Hybrid Automata (PIHA). In these automata there are no resetting maps, while invariant sets are defined by linear inequalities. Therefore, based on the continuity property of the state trajectories in a PIHA, the problem is reduced to finding possible transitions between all two adjacent discrete modes. In the presented method, the possibility and the direction of such transitions are detected only by computing the angle between the vector field and the normal vector of the switching surfaces. Thus, unlike the most other reachability methods, there is no need to solve differential equations and to do mapping computations. In addition, the proposed method, with some modifications can be applied for extracting Stochastic or Timed Discrete Trace Transition Systems.

In order to improve the optimal performance of a machining process, a booster to improve the serve control system performance with high stability for EDM is needed. According to precise movement of machining process using electrical discharge (EMD), adaptive control is proposed as a major option for accuracy and performance improvement. This article is done to design adaptive controller based on self-tuning regulator (STR) using adaptive online detection methods of gradient MIT and normalized gradient MIT to adjust machine's movement time in the control process. Process performance after controller design shows that determined Gaps location at different points is appropriate and improves machining rates almost 100%. In order to improve the optimal performance of a machining process, a booster to improve the serve control system performance with high stability for EDM is needed. According to precise movement of machining process using electrical discharge (EMD), adaptive control is proposed as a major option for accuracy and performance improvement. This article is done to design adaptive controller based on self-tuning regulator (STR) using adaptive online detection methods of gradient MIT and normalized gradient MIT to adjust machine's movement time in the control process. Process performance after controller design shows that determined Gaps location at different points is appropriate and improves machining rates almost 100%.

Orifice flow meter is one of the most common devices in industry which is used for measuring the gas flow. This system includes an orifice plate, temperature and pressure transmitters, and a flow computer. The flow computer is used for collecting information related to temperature, pressure, and their differences under various conditions. Also the flow computer can calculate the flow rate of gas at the standard conditions. Relations used in the flow computer are quite complex and nonlinear and also measurement noise can affect this device easily. Moreover, it needs calibration at different times which is expensive. To replace the flow computer, in this paper, a type-2 fuzzy neural network (T2FNN) has been utilized to calculate the gas flow. The temperature, pressure, and pressure differences are used on either side of the orifice as the inputs of T2FNN and it considers the flow of gas as output. In this paper, the particle swarm optimization (PSO) algorithm has been utilized to train the antecedent and consequent parameters of T2FNN. Using some simulations, it has been shown that the designed T2FNN can measure the flow of gas much better than the type-1 fuzzy neural network (T1FNN) in the presence of a high level of measurement noise.

Influence of distributed generation systems in the distribution systems can increase the level of short-circuit current. The effectiveness of distributed generation systems is affected by the size, location, type of distributed generation systems technology, and the methods of connecting to distribution systems. Wind turbine system is the examples of distributed generation source. Not only does the using of fault current limiter reduce the pressure on network equipment, but also it can provide a connection to improve the function of the system. There are different types of superconducting fault current limiter, which are made of various superconducting materials and with different designs. Superconducting fault current limiter can be categorized as resistive, inductive and bridge. In this research, the effect of superconducting fault current limiter factors investigated on transient recovery voltage, voltage drop and transient behavior of wind turbine systems based on fixed speed wind turbines, in order to study the behavior of all three types of superconducting fault current limiter that was installed in distributed generation systems. The simulation results show that the transient recovery voltage, the voltage drop and the transient behavior of fixed speed wind turbines have been improved using superconducting fault current limiter

The researcher measured the least number of frequency response functions required for the identification of modal parameters, in order to simplify the identification of modal properties of such systems. In this work, the orbital machines are supposed to be a combination of orbital and non-orbital components. Structural Approach specified the identification of dynamic properties only to those phrases that contain responses to a driving force. It has been revealed that the identification of dynamic properties distinguishes the orbital and non-orbital components of the structures and as a result, non-symmetric sections of the space coordinate matrixes become obvious. The application of the above approach was examined on two different structures. The first examination was on a computer-simulated rotor model with four degrees of freedom. In this case, the theoretical properties of this approach were evaluated, while the noise factor was disregarded. The second examination was done on a true machine, whereby the probable problems of the implementation of the suggested approach were clarified. The complete modal identification of an orbital system takes place without the need to measure a complete row of FRF matrixes. The number of the elements to be measured in an FRF matrix depends on the number of degrees of freedom of the system and on the non-symmetric sections of the stuffiness and damping matrixes. The number of elements of the left specific axis that should be measured directly from the evaluated data depends on the matrix sub-ranks, which is composed of non-symmetric sections of space-featured matrixes.

Nowadays, using distributed generation (DG) resources, such as wind and solar, also improving the voltage profile in distribution companies has been considered. As optimal placement and sizing of shunt capacitors become more prevalent, utilities want to determine the impact of the various capacitors placement in distribution systems. Locating and determining the optimal capacity of shunt capacitors in order to reduce power losses and improving the voltage profile and using the maximum capacity of transmission lines, are one of the common problems in the design and control of power systems. Using the shunt capacitors, not only improve voltage profiles, but also reduce system losses. In this study, a genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are proposed for simultaneous placement of capacitors and DG resources in order to reduce power losses and improve the voltage profile in a case study radial distribution network. Simulations applied on IEEE 70-bus and 86-bus test system, and finally solutions of the proposed algorithms are compared.