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This paper presents a new neuro-based method for short term load forecasting of Iran national power system (INPS). A MultiLayer Perceptron (MLP) based Neural Network (NN) toolbox has been develeped to forecast 168 hours ahead. The proposed MLP has one hiden layer with 5 neurons. The effective inputs were selected through a peer investigation on historical data released from the INPS. To adjust the...
In this paper combination of standard and second order sliding mode controller are used and investigated for congestion control problem of differentiated Services (Diff-Serv) networks. Robustness against modeling uncertainties and disturbances are major features of sliding mode controller. Chattering phenomenon affects sliding mode congestion control; to overcome this problem, second order sliding...
In this paper sliding mode controllers (SMCs)' techniques are used and investigated for congestion control problem of differentiated Services (Diff-Serv) networks. Robustness against modeling uncertainties and disturbances are major features of sliding mode controller. Chattering phenomenon affects sliding mode congestion control; to overcome this problem, second order sliding mode control (SOSMC)...
In this paper a new controller for congestion problem in TCP networks has been proposed. Sliding mode controller is robust against modeling uncertainties and disturbances. In sliding mode control states should be reached a predefined surface (sliding surface), in a limited time and remain the same surface over time. Moving on the sliding surface is independent of the uncertainties, so this technique...
Traffic management and adjustment is obviously of great importance in any communication network. Without traffic supervision and control, an increase in demand for network resources can lead to a significant decrease in network service quality and efficiency. Since the most important issue in the field of control theory is stability of dynamic systems, control science can be appropriately applied...
In this paper a feedback linearization is presented that addresses the coupling effects between two groups of electromagnetic trains. The module, based on some reasonable assumptions of nonlinear mathematical model, is modeled as a double-electromagnet system. The proposed algorithm in tracking has a satisfying performance in presence of unknown changes in the mass. It also shows robustness against...
In this paper an adaptive controller is presented that addresses the coupling effects between two groups of electromagnetic trains. The main application of DEM (Double Electro-Magnet) is rapid rail transportation. Since the number of passengers is stochastic, the mass of the train will be variable too. On the other hand, due to the variation of the DEM parameters (such as coil inductance) in a real...
One of the challenges in designing computer networks is "queue management and congestion avoidance". There are several studies for congestion reduction and controlling such as random early detection (RED) and its variants. More recent works on developing congestion avoidance methods include modeling a TCP flow in an active queue management (AQM) of a bottlenecked network link. Rather than...
Being in the category of data driven approaches, both adaptive neuro-fuzzy inference system (ANFIS) and principal component analysis (PCA) have been widely used in literature for fault detection and isolation when the whole things that we know about and have from the systems are some measurements corrupted by noise. In spite of promising applications of both methods, it is an unanswered question that...
Path planning is one of the most important fields of research in the area of robotics. In this paper, a path planning method for a certain type of wheeled mobile robots called automated guided vehicles (AGVs) is proposed. The proposed model applies fuzzy control techniques to navigate multi AGVs in an unknown environment to reach a certain destination. In addition, a new method for escaping local...
In this paper, an analytical method for a design of a congestion control scheme in packet switching network is presented .This scheme is particularly suitable for implementation in ATM Switch Systems, for the support of the available bit rate (ABR) service in ATM networks .The control method is rate based with a local feedback controller associated with each switch node. The controller is a generalization...
Wheeled Mobile Robots are considered as the most widely used class of Mobile Robots. This is due to their fast manoeuvring, simple control methods and energy saving characteristics. A new fuzzy algorithm for path planning of multiple wheeled mobile robots is presented in this paper which is optimal both in sense of travelling time and distance. A new method is proposed to escape a local minimum. The...
Wheeled mobile robots are considered as the most widely used class of mobile robots. This is due to their fast maneuvering, simple controllers, and energy saving characteristics. Two new algorithms for tracking control of these robots are presented in this paper: an adaptive controller and a nonlinear controller. Here, the two algorithms are compared with regarding noise resistance and disturbance...
Wheeled mobile robots are considered as the most widely used class of mobile robots. This is due to their fast maneuvering, simple controllers, and energy saving characteristics. A new adaptive algorithm for tracking control of these robots is presented in this paper which is robust against external and internal disturbances. A combination of model reference adaptive control and gain scheduling is...
This paper presents a neuro-based short term load forecasting (STLF) method for Iran national power system (INPS) and its regions. This is an improved version of the one given in [1]. The architecture of the proposed network is a three-layer feed forward neural network whose parameters are tuned by Levenberg-Marquardt BP (LMBP) augmented by an early stopping (ES) method tried out for increasing the...
Many researchers have investigated short term load forecasting (STLF) in recent decades because of its importance in power system operation. In this paper a multi layers perceptron (MLP) neural network (NN) is designed for load forecasting in normal weather condition and ordinary days. The architecture of the proposed network is a three-layer feedforward neural network whose parameters are tuned by...
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