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Any realistic model will have high complexity; in other words, it will require many state variables to be adequately described. The resulting complexity, i.e. number of first-order differential equations, is such that a simplification or model reduction will be needed in order to perform a simulation in an amount of time which is acceptable for the application at hand, or for the design of a low order...
The applications of The Brush Less Direct Current (BLDC) are increasing day by day. In order to have proper utilization of these motors and to control them effectively it's important to have proper mathematical modeling of these motors. Similarly effective control these motors are also essential to have successful application of the devices across multiple domains. This work addresses both these important...
The open-pit mine vehicle scheduling problems are discussed to assign the mine resource reasonably, adjusting the balance of supply and demand effectively and improving the transportation efficiently, and provide necessary technical support for complete open-pit operational scheduling measures. Meanwhile, we design natural number coding genetic algorithms with the technologies of adaptive adjustment...
When vehicle path is performing express distribution for various branches in distribution center, we adopt simultaneous service of distribution strategy between express delivery and collection. It assumes that vehicles follow normal distribution of travel time among each point. Under condition that distribution branches have soft time window restriction and express delivery collection quantity follows...
To determine investment and cost estimation scientifically and simplify the investment estimating preparation, an improved BP neural network estimation model with GA optimization is proposed, based on the learning process of standard BP neural network. Our scheme set initial weight and whitening positioning coefficient as genetic population. The coefficients are optimized according to the principle...
Proportional-integral-derivative (PID) controller act as efficient controllers for controlling all kinds of industrial process with best performance. A number of chemical processes in the industries are controlled using PID controllers. However, the industrial processes are generally more complicate and nonlinear which can yields inferior performance when controlled by conventional PID controllers...
This paper presents a comparison of some well-known global optimization techniques' performance. The purpose of the comparison is to find the best algorithm for optimization. Parameters optimization was conducted in order to achieve better results in PID fractional controller. The proposed techniques are Genetic algorithm (GA), particle swarm optimization (PSO), culture algorithm (CA) and artificial...
The solution of plant-level optimal load dispatch can effectively improve the economic benefits of the plant. It not only response to the national energy conservation and the strategic needs of sustainable development but also adapt to the electricity's market-oriented reform called “separating form and bidding on power net”. To increase the economic benefits, it is significant for the thermal power...
In this paper it presents a methodology that aims to deliver a near optimal Distributed Generation (DG) in the process of allocation DG units by using a hybrid genetic algorithm, Hence, the main aim is to minimize power losses in DG. The proposed algorithm in this paper involves two main parts of algorithms an artificial neural network (ANN) that found to evaluate the fitness function in the generation...
Battery state of charge (SOC) has to be estimated properly in order to build a good battery management system (BMS) for electric vehicles. A Lithium battery dynamics has nonlinearity element and time varying parameter values. The speed of parameter change is different to each parameter. This paper proposes a new method of SOC estimation based on recursive least square (RLS) algorithm with multiple...
This paper discusses the reduction of real power loss in the distribution system by reconfiguration of the distribution network. Reconfiguration is done by changing the status of the sectionalizing and tie switches. The optimal configuration with minimum real power loss is to be determined. First, the configuration is determined manually and to overcome its limitations, Genetic algorithm (GA) technique...
In this paper, the design of a Proportional-Integral-Derivative (PID) controller for the cruise control system has been proposed. The cruise control system, which is a highly nonlinear, has been linearized around the equilibrium point. The controller has been designed for the linearized model, by taking the dominant pole concept in the closed loop characteristic equation. The PID controller parameters,...
Process control is one of the important problems in today industries. Precise control of level, temperature, pressure and flow is important in many process applications. Now a day's PID controllers have found wide acceptance and applications in the industries. The main objective of this work is to improve the performance of PID controller of water tank system consists of various sensors /transducers...
This paper presents an adaptive neuro fuzzy interference system (ANFIS) trained voltage response for a wind-diesel based isolated hybrid power system (IHPS). The system is studied by introducing 1% random variables as probabilistic pattern with 10% increase in reactive power load demand and wind input power simultaneously. STATCOM is used as dynamic reactive power compensator. The proportional integral...
To optimize generation scheduling of four diesel generators in a planned microgrid, we applied General Algebraic Modeling System (GAMS) and Genetic Algorithm (GA). The aim is to minimize power generation costs which depend on high and volatile diesel prices, and consequently to reduce emissions. A mixed-integer quadratic constrained model for the optimal scheduling was formulated and solved by CPLEX...
In this paper, the PI controller design is presented based on the genetic algorithm. In order to obtain the stability boundary of PI control systems in parameter space, the Tan's method is adopted here. In addition, the genetic algorithm (GA) is applied to fulfill the specifications of integral absolute error (IAE). The proposed method applies on a wind power system and a boiler steam drum process...
In this paper a novel localization technique is proposed using fuzzy logic and genetic algorithm to get nearly precise location of sensor nodes, in a range free localization system. This localization technique gives a stable system in which both magnitude and range of the error are very low. Various membership functions (MF) are tested among which the Sinc MF provides the best results for the system...
The Selective Harmonic Elimination Pulse-Width Modulation (SHE-PWM) is an effective method for harmonic elimination in multilevel inverter. This paper presents the solutions of Selective Harmonic Elimination (SHE) problem based on Genetic algorithm (GA) and Particle Swarm Optimization (PSO) techniques. Total Harmonic Distortion (THD) of output voltage is minimized maintaining selected harmonics within...
In this paper, low frequency oscillations in power system under the different operating conditions have been solved through PID based power system stabilizer. The tuning of the parameters of the PSS are considered as optimization problem, and the parameters are tuned using genetic search algorithm. Here forth-order linear and non-linear model of the synchronous machine (model 1.1) which includes both...
The traditional K-means algorithm is sensitive to the initial points and easy to fall into local optimum. To avoid this kind of flaw, an improved GA-based text clustering algorithm CGHCM is proposed. The new algorithm is proven effective to avoid falling into local optimum and obtains better clustering results.
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