an adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. another key feature of this structure is the fact that, it does not need model of the system. in this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  online training of neurolinearizer is compared to model predictive recurrent training...

FACTS technology has considerable applications in power systems, such as; improving the steady stateperformance, damping the power system oscillations, controlling the power flow, and etc. STATCOM is oneof the most important FACTS devices used in the parallel compensation, enhancing transient stability andetc. Since three phase fault is widespread in power systems, in this paper STATCOM is used...

in this paper, a novel compensator based on magnetically controlled reactor with fixed capacitor banks (fc-mcr) is introduced and then power system stability in presence of this compensator is studied using an intelligent control method. the problem of robust fc-mcr-based damping controller design is formulated as a multi-objective optimization problem. the multi-objective problem is concocted ...

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of t...

The aim of this paper was to present an optimized method in order to use maximum capacity of the photovoltaic panels. In this regard, we presented a method for the maximum power point tracking in the photovoltaic systems by using the neural networks and adaptive controller. In the proposed system, we estimated an error by using neural network. If this error is lower than the allowable systems e...

Power system stabilizers have been widely used and successfully implemented for the improvement of power system damping. However, a fixed parameter power system stabilizer tends to be sensitive to variations in generator dynamics so that, for operating conditions away from those used for design, the effectiveness of the stabilizer can be greatly impaired. With the advent of microprocessor techn...

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these...

In this paper, a consistent pattern with the optimal coordinated design of PSS and SSSC controller to improve the damping of low frequency oscillations is shown. In this design, sensing and signal transmission time delays are considered as effectiveness parameters. The design problem has been considered an optimization problem and biogeography-based optimization (BBO) algorithm is used for sear...

The aim of this paper is to investigate a novel approach for output feedback damping controller design ofSTATCOM in order to enhance the damping of power system low frequency oscillations (LFO). The design ofoutput feedback controller is considered as an optimization problem according with the time domain-basedobjective function which is solved by a honey bee mating optimization algorithm (HBMO...

This paper suggests a method for designing PSS to damp multi-machine power system oscillations.  The method is based on robust control theory. First, the conventional method for designing robust controller in LMI framework is illustrated. Then, the suggested method is given, in which, a PID output feedback controller is tuned using the LMI approach. Mostly, the classical methods are used t...