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.

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.

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.

Multivariable liquid level Control is necessary in process industries to ensure quality of the product and safety of the equipment. However, the significant problems of the Control System include excessive time consumption and percentage overshoot, which result from ineffective performance of the tuning methods of the PID Controllers used for the System. In this paper, fuzzy logic was used to tune the PID parameters to Control a four-coupled-tank System in which liquid level in tanks 1 and 2 were Controlled. Mass Balance equation was employed to generate the transfer function matrix for the System, while a Fuzzy Inference System (FIS) file is created and embedded in fuzzy logic Controller blocks, making tuning rules for the PID. Matlab R2009b simulation of the System model shows that the rise time (RT), settling time (ST), peak value (PV) and percentage overshoot (PO) for the developed DF-PID Controller were 1. 48 s, 4. 75 s, 15 cm and 0% respectively for tank-1; and 0. 86 s, 2. 62 s, 10 cm and 0% respectively for tank-2, which are the smallest and best values when compared with other PID tuning methods namely: Ziegler-Nichols, Cohen-Coon and Chien-Hrones-Reswick PID tuning methods.

In the large scale applications, sometimes it is essential that the Control theories be distributed or Decentralized. In this paper, regarding large scale of power Systems and advantages of model predictive Control (MPC), a constraint predictive Control method that is called “Receding Horizon Control (RHC)”, used for load frequency Control in a two-area power System with two cooperating methods of agents. The main advantage of Decentralized Control is complexity reduction in computations. Moreover, in the application of centralized Control, online computation of inputs (high dimensions) is complex, and non-flexible, and impractical. Finally using of simulations, centralized and Decentralized Control methods, cooperative methods are compared under a variety of disturbances.

This paper presents a variable structure based approach to the load frequency Control System problem in electric power generation Systems. This approach combines the salient features of both variable structure and fuzzy Systems to achieve high-performance and robustness. The Control signal consists of equivalent Control, switching Control and fuzzy Control components. The influence of System nonlinearities such as generation rate constraint and governor dead band is considered. In addition, a Decentralized form of this Controller is applied to a two-area power System. Simulation results show that the System responses are strongly robust for parameter variations.

In this paper, a Decentralized Control strategy based on the separation of the energy generation Control unit is presented, which leads to stable operation and improve the DC micro-grid (MG) dynamic behavior. By applying the proposed Control strategy, the fuel cell (FC) and supercapacitor (SC) units, which form a hybrid distributed generation (DG) source, are simultaneously Controlled with independent Controllers suggesting independent dynamic Control performance. Moreover, in this Control strategy, the SC unit, is supplied with a state-of-charge (SOC) regulator block to keep its proper performance. Accordingly, the dynamic separation of energy units affects the dynamic behavior of the overall DCMG and improves the System damping factor. By using the location analysis method of System eigenvalues, the proposed Control strategy performance is evaluated. Also, the simulation studies in the PSCAD/IEMTDC software environment confirm the feasibility and proper performance of the proposed scheme.

This paper suggests a method for designing PSS to damp multi-machine power System oscillations. The method is based on robust Control theory. First, the conventional method for designing robust Controller in LMI framework is illustrated. Then, the suggested method is given, in which, a PID output feedback Controller is tuned using the LMI approach. Mostly, the classical methods are used to tune a PSS, but in this paper a robust approach is investigated to guarantee the robustness of the given PSS. The performance of the Controller is tested on a sample power System. Simulation results show the effectiveness, robustness, and good performance of the suggested Controller.

Polling System is not trusted everywhere around the world it is very important in this modern world to replace the traditional polling System with the new technology. Some countries like United States, Japan, and India suffer from corrupted polling System. Major issues are faced by current polling Systems like System hacking, vote rigging, vote manipulation, distributed denial of service attack, and online polling booth capturing. This paper will lead to the problems faced by the traditional polling System and how the new technology will provide the solution to that problem. Also, our purpose is to check the feasibility of the System by recording the transaction fees and evaluate the right way to spend the amount of gas in the transaction. This will highlight blockchain frameworks including blockchain as a service and polling System which is on blockchain that addresses all constraint introducing ethereum which is a blockchain-based distributed computing platform. Ethereum is open source, and publicly available with a System featuring smart contracts. It provides the cryptocurrency wallets that let you make cheap, instant payments with gas in the form of ethers. The ethereum community is the most active and largest blockchain community in the world. There is no centralized organization that Controls ethereum.