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In this paper, the stabilization problem of loaded double inverted pendulum using an optimized state feedback sliding mode control is investigated. ADAMS/Matlab co-simulation environment is used for building a virtual nonlinear model for loaded double inverted pendulum system and the state feedback sliding mode control law is designed for stabilizing the system. Mismatched uncertainties represented...
Often times in mobile robotics, optimizing a sequence of tasks and the paths between those destinations is an essential factor. In simple cases, this problem can be modeled by the well-researched Traveling Salesman Problem (TSP). In more complex situations however, the TSP is not a suitable model. In redundant robotic systems, a robot can assume infinitely many configurations while performing each...
Software developers and maintainers often need to locate code units responsible for a particular bug. A number of Information Retrieval (IR) techniques have been proposed to map natural language bug descriptions to the associated code units. The vector space model (VSM) with the standard tf-idf weighting scheme (VSM natural), has been shown to outperform nine other state-of-the-art IR techniques....
This article presents a new Unification Matching Scheme (UMS) for information retrieval using the genetic algorithm. The selection of appropriate matching functions contributes to the performance of the information retrieval system. The proposed UMS executes the Unification function on three classical matching functions for different threshold values. The main objective is to utilize all the base...
Some identification methods of the systems are developed, but there is still some space for finding new solutions for such classic and needed procedure as the identification is. For proposed solution in the paper the genetic algorithms are used as optimization method for finding the parameters of difference equation of systems of the system of 2nd order with defined transfer function, but it can be...
The paper is introducing the principles of a new global optimization strategy, Imperialistic Strategy (IS), applied to the Continuous Global Optimization Problem (CGOP). Inspired from existing multi-population strategies, like the Island Model (IM) approaches to parallel Evolutionary Algorithms (EA) and the Imperialistic Competitive Algorithm (ICA), the proposed IS method is considered an optimization...
In this paper, a technique of combining Lagrangian relaxation (LR) with a differential evolution algorithm (DEA) method (LR-DEA) is proposed for solving unit commitment (UC) problem of thermal power plants. The merits of DEA method are parallel search and optimization capabilities. The unit commitment problem is formulated as the minimization of a performance index, which is sum of objectives (fuel...
Simultaneous pose and correspondence estimation problem is used to determine the pose of a 3D object from a single 2D image when corresponding relation is unknown between 3D object points and 2D image points. The problem arises in many areas of computer vision and some algorithms have been presented. However, all the state-of-art algorithms rely on appropriate initialization and the correct solution...
This paper proposes to use Genetic algorithm for optimizing the best Eigen vectors to improve the recognition accuracy of Modular image Principal Component Analysis (MIPCA) for face recognition. Modular Image PCA has been proved to be efficient in extracting features for recognizing face invariant to large expression. It is important to note that all the extracted features are not efficient and required...
Hybrid algorithms incorporated with parallel processing techniques are very powerful tools for efficiently solving very complex optimization problems. We present asynchronous parallel computer architecture adaptation based on hybridization of Genetic Algorithms (GAs) and Estimation of Distribution Algorithms (EDAs). In this master-slave formulation, slaves perform evolutionary computation independently...
The transformerless DC/AC inverter topologies are employed in Photovoltaic systems in order to improve the power conversion efficiency, power density and cost. The Active-Neutral Point Clamped (Active-NPC) transformerless inverters have the advantage of achieving better thermal balance among their power semiconductors. In this paper, a new modulation technique is proposed for optimally controlling...
In the study of identifying homogeneous regions in remote sensing images, fuzzy clustering is one of the most frequently used algorithms. Commonly used method of fuzzy cluster analysis is the fuzzy C-means algorithm(FCM), which easily traps into local optimal solution. An algorithm combining FCM with genetic algorithms is introduced for aerial remote sensing image fuzzy clustering analysis. The input...
Approximate nearest neighbor (ANN) search provides computationally viable option for retrieval from large document collection. Hashing based techniques are widely regarded as most efficient methods for ANN based retrieval. It has been established that by combination of multiple features in a multiple kernel learning setup can significantly improve the effectiveness of hash codes. The paper presents...
FastICA and Infomax are the most popular algorithms for calculating independent components. These two optimization process usually lead to unstable results. To overcome this drawback, a genetic algorithm for independent component analysis has been developed with enhancement of the independence of the resulting components. By modifying the FastICA to start from given initial point and adopting a new...
Network reconfiguration in electrical distribution system is the process of changing the status of tie or sectionalizing switches, i.e., open or closed status to alter its topological structure. The proposed work attempts to reconfigure the system to balance loads while maintaining system radiality, using Ant Colony Optimization Technique. The burden of over loaded feeders is reduced by shifting partial...
The synthesis of thinned arrays by means of optimization is presented in this paper using compact genetic algorithm (cGA). The optimization algorithm implements a probability vector to represent the population, which is suitable to apply to thinned array problem. Moreover, by introducing some modifications to the original cGA, the peak side-lobe level (PSLL) of the thinned array is well controlled...
An analysis of previously derived Ambisonics decoders shows that the mid-high frequency performance of these decoders has poor agreement with subjective perception, since the optimized decoder coefficients could not well meet the objectives developed by the energy vector, and the polar pattern of speaker feeds is suboptimal. In this paper, new objectives are added to fitness function for the optimal...
For the problem that how to compute objective weight based on personal preference during multi-objective optimization process, this paper proposes a method which decides the objective weights by solving a constrained optimization problem. At first, it transforms the objective weight computation problem into a synthetical fitness optimization problem according to statistics theory, then it transforms...
Virtual machine (VM) placement is a key technologyto improve data center efficiency. Most works consider VM placement problem only with respect to physical machine(PM) or network resource optimization. However, efficient VM placement should be implemented by joint optimization of above two aspects. In this paper, a multi-objective VM placement model to minimize the number of active PMs, minimize communication...
Biogeography-based Optimization(BBO) is a new biogeography inspired optimization algorithm, and it searches for global optimum through two operators: migration and mutation. To alleviate the slow convergence and premature problem of the BBO, a hybrid optimization algorithm based on BBO and differential evolution(DE) has been presented in this paper. In the given hybrid algorithm new habitats in ecosystem...
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