Stochastic uncertainties in complex dynamical systems lead to variability of system states, which can in turn degrade the closed-loop performance. This paper presents a stochastic model predictive control approach for a class of nonlinear systems with unbounded stochastic uncertainties. The control approach aims to shape probability density function of the stochastic states, while satisfying input and joint state chance constraints. Closed-loop stability is ensured by designing a stability constraint in terms of a stochastic control Lyapunov function, which explicitly characterizes stability in a probabilistic sense. The Fokker-Planck equation is used for describing the dynamic evolution of the states' probability density functions. Complete characterization of probability density functions using the Fokker-Planck equation allows for shaping the states' density functions as well as direct computation of joint state chance constraints. The closed-loop performance of the stochastic control approach is demonstrated using a continuous stirred-tank reactor.

Stable operation of LCL filtered grid-connected inverters can be achieved using active damping. However, the stability can be threatened by non-ideal conditions such as delay in digitally controlled systems and grid impedance variation at the point of common coupling (PCC). In a grid-side current controlled inverter, the computational and PWM delays cause an unintentionally negative virtual resistance when the resonance frequency is higher than one-sixth of the sampling frequency (f s /6). This paper proposes a delay compensation method to address this issue which can expand the effective damping region up to Nyquist frequency (f s /2). Also, it is shown that the negative real part of the inverter output admittance will make the system unstable under specific grid condition. Therefore, a PCC voltage feedforward method is proposed to cancel the negative real part of the inverter output admittance according to passivity-based stability. Thanks to the proposed methods, the inverter output admittance will be passive in all frequencies and can be connected to the grid regardless of grid impedance. It means that the inverter has robust plug-and-play functionality. The validity of the theoretical analysis and the effectiveness of the proposed approaches are verified using experimental results on a laboratory prototype. 1

A cost effective off-line method for equivalent circuit parameter estimation of an induction motor using hybrid of genetic algorithm and particle swarm optimization (HGAPSO) is proposed. The HGAPSO inherits the advantages of both genetic algorithm (GA) and particle swarm optimization (PSO). The parameter estimation methodology describes a method for estimating the steadystate equivalent circuit parameters from the motor performance characteristics, which is normally available from the nameplate data or experimental tests. In this paper, the problem formulation uses the starting torque, the full load torque, the maximum torque, and the full load power factor which are normally available from the manufacturer data. The proposed method is used to estimate the stator and rotor resistances, the stator and rotor leakage reactances, and the magnetizing reactance in the steady-state equivalent circuit. The optimization problem is formulated to minimize an objective function containing the error between the estimated and the manufacturer data. The validity of the proposed method is demonstrated for a preset model of induction motor in MATLAB/Simulink. Also, the performance evaluation of the proposed method is carried out by comparison between the results of the HGAPSO, GA, and PSO.

The quality of injected current in multi-paralleled grid-connected inverters is a matter of concern. The current controlled grid-connected inverters with LCL filter are widely used in the distributed generation (DG) systems due to their fast dynamic response and better power features. However, designing a reliable control system for grid-connected inverters with LCL filter is complicated. Firstly, overcoming to system resonances due to LCL filters is a challenging task, intrinsically. This could become worse as number of paralleled grid-connected inverters increased. In order to deal with resonances in the system, damping methods such as passive or active damping is necessary. Secondly and perhaps more importantly, paralleled grid-connected inverters in a microgrid are coupled due to grid impedance. Generally, the coupling effect is not taken into account when designing the control systems. In consequence, depending on the grid impedance and the number of paralleled inverters, the inverters installed in a microgrid do not behave as expected. In other words, with a proper control system, a single inverter is stable in grid-connected system, but goes toward instability with parallel connection of other inverters. Therefore, consideration of coupling effect in the multi-paralleled grid-connected inverters is vital. Designing control systems for multi-paralleled grid-connected inverters becomes much more difficult when the inverters have different characteristics such as LCL filters and rated powers. In this paper, the inverters with different characteristics in a microgrid are modeled as a multivariable system. The comprehensive analysis is carried out and the coupling effect is described. Also, the control system design for multi-paralleled grid-connected inverters with LCL filter is clarified and a dual-loop active damping control with capacitor current feedback is designed. Finally, the proposed multivariable control system for a microgrid with three-paralleled gridconnected inverters with LCL filter is validated by simulation.

Future nanoscale memory technologies must ultimately be able to operate at power supply voltages in the order of 0.6 V or less. We have demonstrated in this work that it is possible to utilize symmetric program-erase (P-E) cycling for Ag/Ag-Ge-S/W programmable metallization cell devices at voltages below 0.6 V and still maintain an OFF/ON resistance ratio well in excess or 10 over a wide range of program and erase currents (0.27, 1.6, 55 and 220 µA) as set by a series resistance. The distributions of resistance values for 10(4) P-E cycles indicate that the margins between the highest on- and lowest off-state resistances are sufficient for unambiguous differentiation in all but the lowest current case in which there is some overlap. In addition, there is no substantial change in switching speed for up to 1.5 × 10(6) P-E operations, the maximum number of cycles attempted in this study.