One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive Control method based on dynamic programming has been used to Design a stabilizing power system and a complementary static var compensator (SVC) Controller. By applying a single line to ground fault in the network, the robustness of the Designed Control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with Controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive Control method based on dynamic programming for the stabilizing Design of the power system and the complementary SVC Controller. The performance of the Control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Non-cooperative intelligent Control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the Designation of a robust decentralized infinite horizon LQR Control system based on the FNEP for a linear time-invariant system. For this purpose, two Control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized Control problem (i.e. an infinite horizon linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented. In the absence of the conditions, by using the least-squares error criterion, an approximated CIHLQR Controller is presented. It is shown that the theorems could be extended from a two-agent Control system to a multi-agent system. Finally, the results are evaluated using the simulation results of a Two-Area non-reheat power system.

A common method for Controlling a group of parallel converters in decentralized Control strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power Control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the Design of micronutrient Controllers. By linearizing and simplifying conditions, the Control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between Control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage Controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power Control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.

Intracytoplasmic sperm injection (ICSI) is one of the most successful techniques of Assisted Reproductive Technology (ART) and is mostly in use for the treatment of infertility with male factors. In this method, before injecting sperm into the intracytoplasmic of the oocyte, cumulus cells around the oocyte must be stripped to facilitate the injection process. To achieve this, both enzymatic and mechanical methods are used in embryological laboratories for denudation, which has major deficiencies, including the possibility of damaging the oocyte prior to the injection process. In this research, a microfluidic-based device is introduced for the separation of cumulus cells around the oocyte with minimum manual operations. The results prove high efficiency, and non-destructive denudation of the oocyte with the reduced amount of culture medium leads to the low-cost preparation process of oocytes. The process can also be integrated with ICSI chips under development and will be reported shortly.

Unfalsified adaptive Control strategy is a data-driven approach in robust adaptive Control that selects the stabilizing Controller from an the available Control bank based on the input-output system’s data. Selection is done without activating the Controllers by using the virtual reference signal and a cost function. Stability of the closed loop system is guaranteed. In this paper, inspired by the unfalsified Control approach, the goal is to select a Controller from the available pre-Designed Controller bank that has the highest level of disturbance attenuation. The selection is based on the system’s data by using a cost function without disturbance measurement. By introducing a new concept called virtual disturbance, the performance of Controllers is evaluated without activation. The convergence of the algorithm and the disturbance attenuation level of the proposed method have been proven in a theorem. Simulation results show performance of the proposed method on a wind turbine for various wind speed disturbances.