The operation of Fuel Cell distributed Generation (FCDG) systems in distribution systems is introduced by modeling, controller design, and simulation study of a Solid Oxide Fuel Cell (SaFe) distributed generation (DG) system. The physical model of the fuel cell stack and dynamic models of power conditioning units are described. Then, suitable control architecture based on fuzzy logic control for the overall system is presented in order to active power control and power quality improvement. A MATLAB/Simulink simulation model is developed for the SOFC DG system by combining the individual component models and the controllers designed for the power conditioning units.Simulation results are given to show the overall system performance including active power control and voltage regulation capability of the distribution system. 

The ability in Unmanned Aerial Vehicle Guidance and control has become an important priority in the air defense field of any country, as one of the modern tools of technology in aerospace systems. In this paper, a group of networked UAVs are considered that follow closely the same objectives. The UAVs communicate with each other and exchange important information such as their velocities and positions with other members in the network. For this purpose, the controller is designed in a distributed approach. Due to the nature of the system, the distributed optimization algorithm is used to implement the network structure as well as to reduce the volume of computation. There are many challenges in the networked system and its optimal solution, such as maintaining optimal arrangement, communication delay and efficient use of energy. It is necessary that the designed controller holds the appropriate performance in the presence of aforementioned challenges. Finally, simulations are carried out in the Matlab software for investigating the performance of the proposed approach. The results indicate a higher rate of convergence and a more acceptable rate of delay compared to previous methods.

This paper presents a robust control scheme for distributed generations (DGs) in islanded mode operation of a microgrid (MG). In this strategy, assuming a dynamic slack bus with constant voltage magnitude and phase angle, nonlinear equations of the MG are solved in the slack-voltageoriented synchronous reference frame, and the instantaneous active and reactive power reference for the slack bus is obtained at each time step, based on Y_bus equation of the MG. The slack bus power references are robustly tracked by the proposed adaptive sliding mode based power controller. In addition, a hyper-plan sliding controller is suggested for other DGs that provides three regulators including active power, reactive power and voltage regulator for DG units and ensures protection of the power electronic interfaces to the faults assumed to have occurred in the MG. At each step time, DGs are modeled as positive and negative current sources that are controlled by their adaptive sliding mode controllers in the normal and abnormal operating conditions. All the parameters of controllers are derived via particle swarm optimization (PSO) algorithm in order to minimize an appropriate cost function. Performance of the proposed control strategy is compared to the performance of the conventional master-slave based control strategy. The validity and effectiveness of the presented method are supported by time domain simulation of a test microgrid in MATLAB.

In this paper, a complete control scheme is developed for an inverter-based distributed generation (IBDG) unit to produce high quality AC voltages in unit terminals. The unit uses a three-phase, four-leg inverter. The control scheme includes a feed-forward current control path and two nested loops, the outer loop for regulating the DG output voltage and the inner one for controlling the inverter current. Proportional-Resonant (PR) controllers are used in the voltage loop to track a sinusoidal reference voltage and eliminate low-order voltage harmonics. The inner current loop is used for over-load protection of the inverter, and improvement of the control system response. The current controller is designed by the state feedback method. The feed forward current control path is used to reduce impacts of load disturbances on the IBDG output voltages. Regarding the role of the inverter output filter and controllers in voltage quality, the filter design procedure is reviewed, the approach to choosing the controllers parameters is explained, and stability conditions of the system are investigated. The performance of an IBDG that supplies a local load is studied under unbalanced and nonlinear loading, and sudden changes in the load amount and voltage amplitude.

This paper proposes a novel distributed adaptive secondary controller for microgrids (MGs) in islanded operation. To enhance the dynamic behaviour of a microgrid considering uncertainties and disturbances, the proposed controller uses a consensus-based adaptive control structure. A novel consensus protocol is proposed to restore the frequency and voltage (f &V) of a microgrid to their rated values. A Lyapunov function is presented to assure the asymptotic stability of the controller and the ultimate boundedness of the global neighborhood consensus error. The nonlinear nature of MGs has been also considered in the algorithm. Unlike other methods in this field that require complete information of distributed generators (DGs), the proposed controller requires only power droop coefficients and is independent of DGs parameters. Different simulations are conducted in MATLAB/SimPower Toolbox on a typical microgrid and under various disturbances to judge the performance of the adaptive controller. The simulation results show the effect of the proposed controller on increasing the resilience of an MG.

distributed supervisory control is a method to synthesize local controllers in discrete-event systems with a systematic observation of the plant. Some works were reported on extending this method by which local controllers are constructed so that observation properties are preserved from monolithic to distributed supervisory control, in an up-down approach. In this paper, we find circumstances in which observation properties are preserved from monolithic to distributed supervisory control. Local observation properties, i.e. local normality and local relative observability are employed for investigating observation properties of each local controller, which are constructed by any localization algorithm that preserves control equivalency to the monolithic supervisor with respect to the plant. These properties enable us to investigate the observation properties from monolithic to distributed supervisory control. Moreover, observation equivalence property is defined according to the control equivalence in a distributed supervisory control with partial observation. It is proved that with preserving observation equivalence of the local controllers to the monolithic supervisor, the control equivalence is satisfied, if and only if the intersection of local event sets is a subset of or equal to the global observable event set.

In this paper, a robust local controller has been designed to balance the power for distributed energy resources (DERs) in an islanded microgrid. Three different DER types are considered in this study; photovoltaic systems, battery energy storage systems, and synchronous generators. Since DER dynamics are nonlinear and uncertain, which may destabilize the power system or decrease the performance, distributed robust nonlinear controllers are designed for the DERs. They are based on the Lyapunov stabilization theory and super-twisting integral sliding mode control which guarantees system stability and optimality simultaneously. The reference signals for each DER are generated by a supervisory controller as a power management system. The controllers proposed in this work are robust, have fast response times, and most importantly, the control signals satisfy physical system constraints. The designed controller stability and effectiveness are also verified using numerical simulations.