نتایج جستجو برای: multi stage controller

تعداد نتایج: 855983  

Microgrids is an new opportunity to reduce the total costs of power generation and supply the energy demands through small-scale power plants such as wind sources, photo voltaic panels, battery banks, fuel cells, etc. Like any power system in micro grid (MG), an unexpected faults or load shifting leads to frequency oscillations. Hence, this paper employs an adaptive fuzzy P-PID controller for f...

In this paper a novel power management method for an electric vehicle (EV) equipped with two energy storage systems is presented. In this way, an optimized nonlinear controller based on fuzzy system is developed. The main stage to design a fuzzy controller is proper determination of fuzzy rules and membership functions that in this paper, the fuzzy rules and input and output membership function...

2012
Zhang Xiaodong

Due to the contradiction between high precision control with complexity of fuzzy controller design, an method for multi-variable fuzzy controller design is presented. A dynamic compensation model for the fuzzy controller is introduced, which simplify the analysis and design of multi-variable fuzzy controller, and improve control performance. The method is applied to high precision water tank te...

2008

In this paper, a new analytical method based on the direct synthesis approach is proposed for the design of a multi-loop proportional-integral-derivative (PID) controller. The proposed design method is aimed to achieve a desired closed-loop response for the multiple-input, multiple-output (MIMO) processes with multiple time delays. The ideal multi-loop controller is firstly designed in terms of...

Journal: :مهندسی قدرت ایران 0
mahmood ebadian university of birjand, iran hamidreza najafi university of birjand, iran reza ghanizadeh university of birjand, iran

in this paper, a novel method is developed for designing the output feedback controller for static synchronous series compensator (sssc). in the proposed method, the problem of selecting the output feedback gains for the sssc controllers is changed into an optimization problem with a time domain-based objective function.then, it is solved by using the particle swarm optimization (pso) algorithm...

2012
Yang Wenchen

This paper presents two optimal approaches of two-stage fuzzy controller for traffic signals at isolated intersections. Firstly, in the light that traffic status variables in two-stage controller leads to the inefficiency of traffic status weakening under low traffic flow, a two-stage combination fuzzy controller is designed from the perspective of structural optimization; this controller intro...

In this paper, a high-performance optimal fractional emotional intelligent controller for an Automatic Voltage Regulator (AVR) in power system using Cuckoo optimization algorithm (COA) is proposed. AVR is the main controller within the excitation system that preserves the terminal voltage of a synchronous generator at a specified level. The proposed control strategy is based on brain emotional ...

2014
Seyed Ebrah im Ghasemi Misagh Imani Ali Zolfagharian

Chaotic vibration has been identified in the flexible automotive wiper blade at certain wiping speeds. This irregular vibration not only decreases the wiping efficiency, but also degrades the driving comfort. A reliable nonlinear system identification namely nonlinear auto regressive exogenous Elman neural network (NARXENN) was adopted in first stage of this survey to model the flexible dynamic...

B. Mirzaeian, M. Moallem, V. Tahani and Caro Lucas,

In this paper, a new method based on genetic-fuzzy algorithm for multi-objective optimization is proposed. This method is successfully applied to several multi-objective optimization problems. Two examples are presented: the first example is the optimization of two nonlinear mathematical functions and the second one is the design of PI controller for control of an induction motor drive supplie...

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...

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