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In this paper we present a new control strategy of wind turbine, by controlling the pitch angle that must be regulated to capture the maximum of power using PID controller and particle swarm optimization, the problem is to identify the PID controller parameters employing the PSO technique. This study makes a mathematical model, which is used to control the power characteristics of the turbine, a comparison...
This paper presents the self-tuning PID parameters by applying Artificial intelligence(AI) algorithm for tuning the Brush DC motor. This proposed approach combines with two algorithms, so called the NN-GA, which are the Neural Network (NN) and the Genetic algorithm(GA). To show the effectiveness of the designed approach, the simulation results are then given. In addition, the simulation results are...
The major problem in permanent Magnet Synchronous Motor (PMSM) drive systems is its nonlinear behavior which arises mainly from motor dynamics and load characteristics. The presence of uncertainties further makes their control an extremely difficult task. So, the speed control strategy should be adaptive and robust for successful industrial applications. The conventional proportional integral derivative...
Music is a performing art that put varieties of sound together to form a sequence of sound that people will find it interesting. In past, only those with certain level of musical knowledge were able to compose music as it is very time consuming to learn and practice musical instruments. Since the advent of modern computing, various methods were introduced to help music composition, such as Markov...
The paper is focusing on dynamic transmission network expansion planning (TNEP). The TNEP problem has been approached from the retrospective point of view. To achieve this goal, the authors are developing two software-tools in Matlab environment. Power flow computing is performed using conventional methods. Optimal power flow and network expansion are performed using artificial intelligence methods...
This paper presents an application of cognitive networking paradigm to the problem of inter-cell interference coordination (ICIC) in Long-Term Evolution-Uplink (LTE-UL). We describe state-of-the-art, research challenges involved, and a novel random neural network (RNN) based power controller and interference management framework. The RNN based cognitive engine (CE) learns how the electromagnetic environment...
Measurement-based load modeling is a promising approach to reliably represent load behavior in dynamic simulations of large power systems. This paper presents a methodology that starts with the acquisition of voltages and currents from power quality monitoring systems and highlights the issues associated with selecting, processing and resampling the data to estimate the relationship between the power...
The balancing of an inverted pendulum by moving a cart along a horizontal track is a classic control problem. The direct approach to solve this problem is to use a control system which derives inputs from two observable parameters, which are error in the pole angle and deviation of cart position from the centre of the track. The proportional, integral and derivative aspects of these measures shall...
Police Patrol is a very useful method for managing the social security. Many researches focus on how to obtain the best strategy for police patrol. We got this research topic from The Sixth National Post-Graduate Mathematical Contest in Modeling. In the proposed approach, Greedy Policy and Randomized Strategy are combined with Genetic Algorithm to solve these problems, simulation result shows the...
Optimal Power Flow (OPF) is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming, Newton-Raphson and Non-linear Programming were previously offered to tackle the complexity of the OPF. However, with the emergence of artificial intelligence, many novel techniques...
The major source of inaccuracy in dynamic power simulations arises from the models used to represent loads, due to their stochastic nature. Nevertheless, measurements of the electrical system dynamic response are available from a large number of sources like power quality monitors and other disturbance monitoring devices. That means that real world recorded data may be used to fit a mathematical description...
A holistic understanding of genetic interactions is crucial in the analysis of complex biological systems. However, due to the dimensionality problem (less samples and large number of genes) of microarray data, obtaining an optimal gene regulatory network is not only difficult but also computationally expensive. In this paper, a Bayesian model for the genetic interactions using the Minimum Description...
Biogas plants are reliable sources of energy based on renewable materials including organic waste. There is a high demand from industry to run these plants efficiently, which leads to a highly complex simulation and optimization problem. A comparison of several algorithms from computational intelligence to solve this problem is presented in this study. The sequential parameter optimization was used...
This paper presents an improved fuzzy logic controller technique parameters estimation, based on genetic algorithm. It is kwon, that fuzzy control rules for a control system is always built by designers with trial and error and based on their experience on some preliminary experiments. We use a genetic algorithm (GA) based methods to generate a satisfactory fuzzy rule base spontaneously. The proposed...
Most flying-wing aircrafts are static and dynamic unstable due to the lack of conventional stabilizers to control the plane in the longitudinal and the lateral directions, and the lateral-directional motion of the static instability flying-wing will cause the coupled longitudinal motion, so the control system is more complicated to design. With this motivation, the longitudinal and lateral-directional...
this paper proposed an improved Gene Expression Programming, and applies it in IDSS, implements GEP Based Intelligent Model Base System (GEP-IMBS), and studies GEP Based Intelligent Model Base GEP-IMBS. GEP-IMBS is a true intelligent Model Base constructing system. In GEP-IMBS, both the types and parameters of model are determined automatically by the system itself.
This work aims to develop an artificial intelligence for a helicopter pilot. That is, a system that learns to fly a helicopter the way a human pilot would. It draws on the benefits of using inverse simulation and genetic algorithms to model systems similar to human process. The goal is to define tasks for the helicopter and have the pilot find control settings that carry out those tasks. The inverse...
The aim of test paper composing is to compose an optimization test paper that satisfies the parameters which the user inputs, so the test paper composing problem is a classical multi-objective linear programming problem. After analyzing the mathematical model of the test paper composing problem, this paper converted part of the restricting conditions of test paper composing problem to objective function,...
In this paper, a new method for designing a particular brace system is proposed. This type of brace system, which is called Non Geometric Brace system are mostly used in seismic area and it allows architects to have more opening in the panel. Non-straight diagonal member of this system introduces eccentricity and it is connected to the corner of the frame by a third member.In designing this system,...
Methods of artificial intelligence have been widely used in the study of investment related topics, and the methods adopted include genetic algorithm and neural network, etc. However, as different to the methods taken in the past, support vector machine is adopted in this article to perform investment strategy study for domestic stock market; investment strategy can be divided into three strategies...
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