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The different nature of the energy resources requires high reliable converters and inverters to supply regulated power to the end customer and to ease its integration within a microgrid. In this paper, modeling, design and control of inverters are presented. The study addresses the feasibility of the single loop and double loop control of inverters. The bodeplot technique is used to analyze the system behavior when the inductor and the capacitor currents are used as feedback signals. The different output impedance natures affect the power sharing between inverters and stability. Therefore, a proposed virtual impedance is implemented to enhance the control performance. Simulation results are presented to show the validity of the control strategy

PID control is widely used in industrial applications although it is a simple control method. Stability of PID controller can be guaranteed theoretically, and zero steady-state tracking error can be achieved for linear plant in steady-state phase. Computer simulations of PID control algorithm have revealed that the tracking error is quite often oscillatory, however, with large amplitudes during the transient phase. To improve the performance of the PID controllers, several strategies have been proposed, such as adaptive and supervising techniques. Fuzzy control methodology is considered as an effective method to deal with disturbances and uncertainties in terms of ambiguity. Fuzzy PID controller combining fuzzy technology with traditional PID control algorithm to become more effective in artificial intelligence control [1],[2]. The most common problem resulted early depending on the complexity of Fuzzy Logic Control (FLC) is the tuning problem. It is hard to design and tune FLCs manually for the most machine problems especially used in industries like nonlinear systems. For alleviation of difficulties in constructing the fuzzy rule base, there is the conventional nonlinear design method [3] which was inherited in the fuzzy control area, such as fuzzy sliding control, fuzzy scheduling [4],[5], and adaptive fuzzy control [6],[7]. The error signal for most control systems is available to the controller if the reference input is continuous. The analytical calculations present two-inputs FLC employing proportional error signal and velocity error signal. PID controller is the most common controller used in industries, most of development of fuzzy controllers revolve around …

The new method of proportional‐integral‐derivative (PID) controller is proposed in this paper for a hybrid fuzzy PID controller for nonlinear system. The important feature of the proposed approach is that it combines the fuzzy gain scheduling method and a fuzzy fed PID controller to solve the nonlinear control problem. The resultant fuzzy rule base of the proposed controller contains one part. This single part of the rules uses the Takagi–Sugeno method for solving the nonlinear problem. The simulation results of a nonlinear system show that the performance of a fed PID Hybrid Takagi‐Sugeno fuzzy controller is better than that of the conventional fuzzy PID controller or Hybrid Mamdani fuzzy FED PID controller.

The design of controllers for nonlinear systems in industry is a complex and difficult task. The development of nonlinear control techniques has been approached in many different ways with varied results. One approach which has shown promise for solving nonlinear control problems is the use of fuzzy logic control. This thesis proposes a new method utilizing proportional–integral-derivative (PID) control as a hybrid fuzzy PID controller for nonlinear system. The salient feature of the proposed approach is that it combines the fuzzy gain scheduling method and a fuzzy Fed PID controller to solve the nonlinear control problem. The resultant fuzzy rule base of the proposed controller contains one part for a non optimized controller. This single part of the rules uses the Takagi-Sugeno method for solving the nonlinear problem and compares it to the mamdani method. The number of fuzzy rules are minimized using a method of series reduction fuzzy rule base. The simulation results of a nonlinear system show that the performance of a Fed PID Hybrid Takagi-Sugeno fuzzy controller is better than that of the conventional fuzzy PID controller or Hybrid Mamdani fuzzy Fed PID controller, especially using the reduction of the number of fired rules.