Research subject: Energy is an integral part of human life and from the beginning of history, mankind is looking for a way to control it to provide the basic needs. One of the available energy sources is fossil energy that has been considered due to the huge amount of energy. Microbial fuel cell is a bioreactor which converts the chemical energy stored in chemical bonds of the organic compounds to electrical energy through the catalytic reactions. Research approach: In this paper, two types of classical PI and MPC Controller are used to investigate the voltage control of a two chamber microbial fuel cell using the model which has been presented by Esfandyari et al. [1, 2]. Considering the features of the proposed model, it can be used to optimize and control the MFC in continuous and batch modes. For this purpose, a classical PI Controller based on internal model and MPC Controller was designed and implemented. Based on the designed Controllers, the adjustment of substrate input flow rate was implemented considering the distribution such as substrate input concentration or the uncertainty of the process model parameter such as Ks and rmax. Main results: For to control the output voltage, step change of 5 units was made in setpoint (inlet flowrate to anode chamber). The values of absolute integral error, rise time and overshoot for the classical PI Controller were 3. 75, 13. 159, and 0. 091, respectively, while these values were 0. 035, 11. 908, and 0. 142, respectively for the MPC Controller. Considering the achieved data, it can be concluded MPC Controller performed better than the classic PI Controller.

A proper linear fuzzy PI Controller is designed in order to achieve a response with specific overshoot and settling time for higher order systems. First, a new design method of this type Controllers is given for a second order systems. Then, its extension is discussed for third order systems. Finally, with the ideas developed, the given design algorithm is generalized to higher order systems.

In this paper, the driver with antiwindup and fuzzy high-performance and robust PI Controller has been suggested for Permanent Magnet Synchronous Motor (PMSM). This Controller is suggested for the design of the robust driver for three phase PMSM and the cost reduction of its control system. It’s useful for the industrial application and automation and ultimately speed control and the improvement of the dynamic behavior of the PMSM. Antiwindup control strategy prevents the increase of the output beyond its saturation point. So, it avoids the saturation. In effect, the suggestion of this new speed control scheme is in line with a goal to realize a better antiwindup scheme. The simulation results are shown for PMSM for two cases of antiwindup control strategy and fuzzy control strategy and with different operation modes. For this purpose, different three phase PMSM output waveforms are presented. These waveforms are presented for fuzzy control strategy in constant torque, constant speed and different reference speeds with focus on speed curve, electromagnetic torque and phase currents.

This paper proposes a new PI/PID Controller tuning method within filtered Smith predictor (FSP) configuration in order to deal with various types of time delay processes including stable, unstable and integrating delay dominant and slow dynamic processes. The proposed PI/PID Controller is designed and tuned based on the IMC principle and a new constraint without requiring any approximation or model reduction techniques. To have an enhanced disturbance rejection for integrating processes, an improved IMC filter is adopted to design a PID Controller. Meanwhile, the set-point weighting method plays a vital role in achieving satisfactory performance in both servo and regulatory problems. The trade-off between robustness and regularity performance is easily adjustable by tuning only one parameter. Simulation results corroborate the effectiveness of the proposed method based on different performance indices including IAE, total variation, overshoot and the maximum peak of error performance indices.

In this paper, the fuzzy proportional- integral Controller (PI) optimized by particle swarm algorithm is applied to control the frequency of island Micro-grids. Micro-grids are distributed energy sources that usually use renewable energies in order to produce and transmit electrical power to distributed loads in both connected and islanded modes. Because of natural variations of power that produced by renewable energy sources and uncertainties of power systems, classic Controllers do not have a good performance. So nominal values of PI parameters and interval of fuzzy membership functions are optimized using PSO algorithm. Fuzzy system updates PI parameters momently. Simulations show the better performance of proposed Controller in terms of RMS, overshoot and undershoot, frequency of oscillations and settling time in facing different load disturbances in comparison to classic PI Controller, fuzzy PI Controller and another PSO fuzzy Controller. Results indicate the robust performance of the proposed Controller in dealing with variation of system parameters.

Today, vehicles are increasingly equipped with brushless DC permanent magnet motors due to the nature of sensorless operation. BLDC motor Controllers can operate the effective speed and position control in a closed loop feedback system without a position sensor mounted on the shaft. The fractional order PID Controller is one of the most common examples of a feedback control algorithm used in many control processes. The BLDC sensorless motor drive has better optimal control over the rotor speed and accuracy with the help of PID fractional Controller (FOPID). In this paper, using two meta-heuristic optimization algorithms, the FOPID control parameters including sitting time, rising time, overload and step response stability of the mentioned system were optimized. The results show that the PMBLDC stepper motor response using the proposed genetic algorithm provides better control performance compared to other available methods.

In recent years, wind energy becomes one of the most important sources for electricity production. For instance it is predicted that the installed wind capacity in China will be about 40 GW till 2020. The permanent magnet synchronous generators (PMSG) which contains of a permanent magnet that causes DC excitation current in the windings, are widely used in wind turbines. The advantage of this type of generators in comparison to the others, are higher efficiency, controllable terminal voltage and reactive power. It is also noticeable that the PMSG speed can be controlled by the converter which leads to MPPT implementation. The MPPT is always implemented to control the generator speed and output power between the cut-in and nominal wind speed. It is necessary to control the generator speed by pitch or stall control for upper rated wind speeds. In this paper after explaining the structure and components of a typical wind turbine with permanent magnet synchronous generator, designing of an offline DMC (Dynamic Matrix Control) and a gain scheduled PI pitch Controller are presented. Both of these Controllers have been tested on the practical simulator of 100 KW wind turbine with PMSG generator and the results are presented and compared.

This paper presents an application of self tuning fuzzy control technique for a Switched Reluctance Motor (SRM) Drive. In this research, the output-scaling factor (a) is adjusted in online by the gain tuning Fuzzy Logic Controller (GTFLC) rules according to the current status of SRM. The rule base of GTFLC for tuning the output SF is defined on error (e) and change of error (De) of the controlled variable using triangular equally overlapped membership functions (MF's). The proposed self-tuning technique is applied to PI- type FLC to conduct real time implementation of speed control for SRM. The proposed scheme shows a remarkably improved performance over its conventional PI type FLC. A prototype based on a 6/4 pole SRM drive has been constructed and used to practically verify the features of the proposed control strategy. The complete speed control algorithm of the SRM drive incorporating the STPIFLC is experimentally implemented and validated using a high-speed digital signal processor board TMS320F2812. It is shown that the presented STPIFLC for SRM drive is with fast tracking capability, less steady state error, robust to load disturbance and very less torque ripple.

Usage of the flywheel energy storage system (FESS) is a common method for frequency regulation due to its high power injection capacity and long life time. FESS is equipped by two back-toback inverters, including grid-side inverter and machine-side inverter. In the conventional method, the machine-side inverter sets the active power and machine flux while grid-side inverter sets the reactive power and common DC bus voltage by conventional PI current Controllers. Especially for frequency regulation, FESS is constantly faced with the change of power and operating point but PI Controller performance is dependent on the operating point of the system. In this paper, at first, the control of both active and reactive power is moved to grid-side inverter and control of DC bus voltage and machine flux is moved to the machine-side inverter. Then, a modified version of the fuzzy PI Controller is proposed for grid-side inverter control in which rated PI Controller coefficients values are optimally designed for rated operating point by feed-back linearization and pole placement then fuzzy system (FS) is used for PI coefficients variation around the rated values when operating point changes. Experimental results verify the performance of the proposed FESS control system for AUT microgrid frequency regulation and also move the DC bus voltage control to the machine-side inverter.