Distributed generations that are connected to the network via a converter, employ dq current control method to control their active and reactive power components in grid-connected mode. In this paper a simple lead-lag control strategy is proposed for a Distributed generation (DG) unit in island mode. When it is connected to the utility grid, the DG is controlled by a conventional dq-current control strategy for active and reactive power components. Once the islanding occurs, the dq-current Controller is disabled and the proposed Controller is used in order to for control of the DG unit operating with its local load. The problem of tuning of Controller parameters is converted to an optimization problem with a time-domain objective function which is solved by a genetic algorithm. To achieve a robust performance ITAE criterion is used as objective function. The robustness of Controller is proved by zero-pole diagram and frequency domain analysis. Simulations results under different operating conditions verify robustness of Controller in comparison with a classical d-q based Controller. The results reveal that the proposed control strategy has an excellent capability in achieving good robust performance and greatly enhances the dynamic stability of the system against load parameter uncertainties.

In the family of Flexible AC Transmission Systems (FACTS) Controllers, the Distributed power flow Controller (DPFC) can control powerfully all the system's parameters like bus voltages magnitude, transmission angle, and line impedances with high redundancy and a wide range of compensation. In this paper, IEEE-14 bus IEEE-30 bus, and IEEE-118 bus systems are taken for the testing of the proposed approach. The optimal placement of the series and shunt converters of the DPFC is decided by the most critical bus and most critical line associated with that bus respectively. The sizing of the DPFC is decided based on the minimization of active power losses of the systems. The loss function is considered an objective function and the limits of the bus voltages magnitudes, bus voltage angles, thermal limits of the lines, and level of compensation of the DPFC are taken as the system's constraints. To solve complex problems in various fields, meta-heuristic optimizations are more popular. Among the meta-heuristic optimizers, the jellyfish optimizer is one that is based on the behavior of jellyfish in the ocean. The optimization of the objective function with constraints has been solved by time-varying acceleration coefficients (TVAC) particle swarm optimization (PSO), artificial bee colony (ABC), genetic algorithm (GA), and metaheuristic optimizer jellyfish methods. Results show that all the optimization techniques provide solutions with minimum losses. Among these methods, the solution of the jellyfish optimizer has the lowest active power losses, highest convergence rate, less number of iterations, and also takes less computational time.

Musculoskeletal disorders caused by heavy workloads are very common in workers, which negatively affects workers' health and productivity. In this regard, the idea of designing an exoskeleton robot is proposed. This robot is similar to a dress which worn on the user's body and parallels the body, accompanying and helping the person. In this paper, the parallel Distributed compensation control method is proposed to be applied to a four degrees of freedom exoskeleton waist robot. Initially, the dynamical equations governing the system are extracted. According to the nonlinear nature of the system, the parallel Distributed compensator Controller is designed with a Takagi-Sugeno linearization approach. The closed loop system response of this Controller is investigated in the Simulink environment of the MATLAB software. The results show that the Takagi-Sugeno linearization approach accurately estimates the nonlinear system, and also the proposed Controller perfectly intercepts the optimal closed loop response.

The ever-increasing of renewable Distributed generation sources in distribution networks, as well as increasing network size, have faced agent-based protection schemes with a heavy communicational load. Accordingly, despite the fast and reliable nature of multi-agent systems, they have the possibility of improper performance, especially in centralized protection systems. This paper presents an intelligent self-healing method that has the ability to replace common multi-agent systems during fault conditions. Therefore, protection tasks are performed in a single control level, without dependence on higher communicational levels, to clear the fault. Decentralized operation of this structure is provided by using intelligent electronic devices and Distributed communications. In this way, the proposed scheme is described with high-speed peer-to-peer communication capability using the IEC-61850 GOOSE protocol. Then, a penetration-free algorithm, without the help of a central Controller, is provided by using GOOSE message capabilities, to prevent any electricity interruption due to insufficient protection settings. Finally, by planning different scenarios and simulating a practical distribution network via ETAP software, the accuracy of the proposed algorithm has been proven.

In recent years, a new generation of networks called software defined networks (SDN) has been introduced whose main focus is on separating control logic from hardware and concentrating it on a central software called the "Controller". SDN improves the network efficiency and reduces the expenses. Despite numerous advantages, SDN faces a lot of challenges such as scalability and reliability that can be fixed through physical decentralization of the control level and introduction of Distributed Controllers. However, the Distributed Controllers also face challenges including scalability, stability, and coordination strategy. This research deals with the improvement of Distributed Controllers’ scalability using the concept of load balancing. For this purpose, we have suggested that a Controller load detection function (CLDF) be placed on each of the related Controllers, and if the load exceeds the threshold level, the new load be transferred to a Controller with the least load. The suggested method is implemented on the Floodlight Controller in a Distributed manner, and implemented on Ubuntu 14. 04 operating system using the mininet simulation platform. The simulation results show that suggested method causes an average growth of 31. 6 percent on the transition rate.

In this paper the power flow control at power systems in the presence of Distributed generation is analyzed. The work proposes use of Unified power flow Controller (UPFC) to control the power flow at the load bus by Main supply in coordination with DG source. This work shows that using UPFC leads to the reduction of the oscillation power and voltage at the time of three phase fault in the system. The studies are performed based on the well known software, MATLAB/SIMULINK Simulation results show that the stability and effectiveness of the applied operation of DG source in coordination with the main utility can be achieved by using UPFC.

Active and reactive power components of a Distributed Generation (DG) is normally controlled by a conventional dq-current control strategy however, after islanding the dq-current which is not able to successfully complete the control task is disabled and a lead-lag control strategy based optimized by simulated annealing is proposed for control of DG unit in islanding mode. Integral of Time multiply by Absolute Error (ITEA) criterion is used as cost function of simulated annealing in order to achieve smooth response and robust behavior. The proposed Controller improved robust stability margins of the system. Simulations with different load and input operating conditions verify advantages of the proposed Controller in comparison with a previously developed classic Controller in terms of robustness and response time.

The body freedom flutter phenomenon is one of the aeroelastic instabilities that occurs due to the coupling of the aeroelastic bending mode of the wing with the short-period mode in the flight dynamics of the aircraft. By using the aeroservoelastic model and applying closed loop control, this phenomenon can be suppressed in the operating conditions of the aircraft and the velocity of this event can be increased. The simplest model aircraft capable of displaying this instability includes the flexible wing and the planar flight dynamics model. For this purpose, the wing structure is modeled using the Euler-Bernoulli beam and, the theory of minimum variable state is used to model unstable aerodynamics to make the conditions suitable for modeling the system in state space. In the control section, the elevator is used as the control surface and LQR theory with Kalman filter is used to body freedom flutter suppression. Finally, the effect of adding a closed loop control to increase the body freedom flutter velocity and the limitations of this work are studied.

Today, in many control methods, neighboring system information is used for better control and synchronization between different units, and therefore, in the access and transmission of information through communication links, problems such as disruption, uncertainty, noise, delay, and cyber-attacks occur. In this paper, the effect of the Denial of Service (DoS) cyber-attack on the microgrid in island mode is investigated and a cooperative Distributed hierarchical Controller is designed with the presence of this cyber-attack. Distributed Generations (DGs) have been analyzed with the help of multi-agent systems and the communication network between them using graph theory. The effects of the DoS cyber-attack on the model of DGs are mathematically formulated and in proving the stability and synchronization of frequency and voltage, the suitable Lyapunov function is presented and the stability analysis of DGs against these cyber-attacks is performed and the stability and synchronization conditions of DGs are proved. To confirm the proposed theoretical issues, a case study model is simulated despite the DoS attack on the communicative links in Matlab Simulink, and the results show the performance of the designed Controller in different conditions.

Software Defined Network (SDN) is a new architecture for network management and its main concept is centralizing network management in the network control level that has an overview of the network and determines the forwarding rules for switches and routers (the data level). Although this centralized control is the main advantage of SDN, it is also a single point of failure. If this main control is made unreachable for any reason, the architecture of the network is crashed. A Distributed denial of service (DDoS) attack is a threat for the SDN Controller which can make it unreachable. In the previous researches in DDoS detection in SDN, not enough work has been done on improvement of accuracy in detection. The proposed solution of this research can detect DDoS attack on SDN Controller with a noticeable accuracy and prevents serious damage to the Controller. For this purpose, fast entropy of each flow is computed at certain time intervals. Then, by the use of adaptive threshold, the possibility of a DDoS attack is investigated. In order to achieve more accuracy, another method, computing flow initiation rate, is used alongside. After observation of the results of this two methods, according to the described conditions, the existence of an attack is confirmed or rejected, or this decision is made at the next step of the algorithm, with further study of flow statistics of network switches by the perceptron neural network. The evaluation results show that the proposed algorithm has been able to make a significant improvement in detection rate and a reduction in false alarm rate compared to closest previous work, besides maintaining the average detection time on an acceptable level.