Journal of Majlesi Journal of Mechatronic Systems
Volume:3 Issue: 4, Dec 2014

In this paper, a new approach for modulation of an 11-level cascaded multilevel inverter using selective harmonic elimination (SHE) is presented. The dc sources feeding the inverter are considered to be varying in time. This method obtain switching angles offline for different dc source values. Then, artificial neural networks are trained to determine the switching angles that correspond to the real-time values of the dc sources for each phase. In fact, each one of the dc sources can have different values at any time, but the output fundamental voltage will stay constant and the harmonic content will still meet the desired specifications. Mathematical methods for harmonic elimination are presented in some of the literatures but solving a non-linear transcendental equation set describing the SHE problem using these methods are not suitable for high level inverters. In this paper, genetic algorithm (GA) and harmony search algorithm (HSA) are applied to obtain the switching angles. These techniques can be applied to cascaded multilevel inverters with any number of levels. This paper gives details on the both evolutionary methods. Finally, the results obtained using GA and HSA are compared together and artificial neural networks are trained for the best answer between GA and HSA.

Advent of electric vehicles in power systems has a variety of effects. The most important effect of electric vehicles in the power system, is related to increase of demand due to charging process (G2V) and also power injection to grid (V2G). In this paper unit commitment problem has been solved considering electric vehicles. Since charging and discharging of electric vehicles depends on factors such as electricity price, fuel price, the rate of charging and discharging as well as the overall behavior of car owners, to cover these uncertainties, both probabilistic modeling and fuzzy sets theory are used. In probabilistic modeling of consumption and generation of electric vehicle in each hour, the number of Evs, the rate and start time of charging and discharging process, and the average distance traveled by each Ev is considered. Since fuzzy modeling can be used in cases that historical data is not available, in second part of this paper a fuzzy number has been assigned to determine the power generation or consumption related to Evs in each hour which is need to solve unit commitment problem. A 10-unit IEEE test system is considered for simulation with 50,000 gridable vehicles using a hybrid GA-ICA algorithm and then the results of probabilistic and fuzzy modeling are compared with each other.

The paper introduces a cable-driven parallel robot which is widely being used in stadium complexes. Kinematics and dynamic equations of this robot are presented. Then, in order to control of the robot, a sliding mode control method is proposed. This algorithm is a simple approach to robust control of nonlinear systems such as robots. In fact, this proposed control method allows nth-order problems to be replaced by equivalent 1St-order problems. The properties of the controller such as good performance tracking, disturbance rejection, and insensitivity to parameter variations are demonstrated by simulation. This controller requires the robot system states to be available. Therefore, the extended Kalman filter is employed to observe those states.

This article introduces the reader to the performance limitations of micro electro mechanical gap-tuning capacitors fabricated in the commercially PolyMUMPs (Polysilicon Multi-user MEMS Process) foundry. And the advantages of the CMOS technology to fabrication of MEMS tunable capacitors are discussed. Also to increase the both of tuning range and quality factor, a three-plate MEMS tunable capacitor with two movable plates is designed and simulated. The simulation of the capacitor was done using the EM3DS software which is demonstrated wide tuning range (300 percent), that is 6 times higher than tuning range of the conventional parallel plate capacitor. The proposed capacitor are designed by using the ALCU metal layers of TSMC 0.18 μm CMOS technology that have caused decreasing the series resistance and increasing the quality factor to 300 in 1 GHZ.

Fixed gains proportional plus integral (PI) controller which gains are chosen by trial and error method has been implemented in industrial applications for the speed control of ac drives. But the high performance of vector control (VC) interior permanent magnet synchronous motor (IPMSM) cannot be achieved with eliminating the overshoot for step change of desired speed and disturbance load torque by using only a set of fixed gains of PI controller. Moreover, the performance of desired speed becomes unsatisfactory due to the utilization of fixed gain PI controller against the variation of load torque and parameters. The performance and robustness of conventional PI controller can be improved by online tuning of PI controller gains. Therefore, an online gains tuning method of PI controller based on fuzzy logic is proposed in this paper for speed control of IPMSM taking core loss into account. The efficacy of the proposed controller is verified by computer simulation. The simulation results show that the overshoot and steady state error can be overcome by using the proposed controller. Besides this, the proposed controller enables to provide excellent performance against the variations of load torque and parameters.

In this paper, The objective is to generate and optimize the fuzzy membership functions for an automotive cruise control in order to obtain a better and faster response facing with the changes in the driving conditions. The regular method for optimization is gradient descent, but in this paper, we use the extended Kalman filter (EKF) in a special manner to optimize the membership functions and also modify the membership function. We will show that the EKF is a powerful method for increasing the performance of a fuzzy system.