Search results for: Control Algorithm.

Authors: Sayeed Salam

Abstract:

This paper presents an efficient emission constrained hydrothermal scheduling algorithm that deals with nonlinear functions such as the water discharge characteristics, thermal cost, and transmission loss. It is then incorporated into the hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Keywords: Emission constraint, Hydrothermal coordination, and Hydrothermal scheduling algorithm.

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Authors: Chun-Yao Lee, Yi-Xing Shen

Abstract:

This paper presents an application of particle swarm optimization (PSO) to the grounding grid planning which compares to the application of genetic algorithm (GA). Firstly, based on IEEE Std.80, the cost function of the grounding grid and the constraints of ground potential rise, step voltage and touch voltage are constructed for formulating the optimization problem of grounding grid planning. Secondly, GA and PSO algorithms for obtaining optimal solution of grounding grid are developed. Finally, a case of grounding grid planning is shown the superiority and availability of the PSO algorithm and proposal planning results of grounding grid in cost and computational time.

Keywords: Genetic algorithm, particle swarm optimization, grounding grid.

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Authors: R. Srinivasa Rao, S. V. L. Narasimham

Abstract:

This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Plant growth Simulation Algorithm (PGSA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 9, 34, and 85-bus radial distribution systems. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution.

Keywords: Distribution systems, Capacitor placement, loss reduction, Loss sensitivity factors, PGSA.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Keywords: Distributes estimation, sensor networks, adaptive filter, IDLMS.

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Authors: Kazuo Komatsu, Hitoshi Takata

Abstract:

In this paper we consider a nonlinear control design for nonlinear systems by using two-stage formal linearization and twotype LQ controls. The ordinary LQ control is designed on almost linear region around the steady state point. On the other region, another control is derived as follows. This derivation is based on coordinate transformation twice with respect to linearization functions which are defined by polynomials. The linearized systems can be made up by using Taylor expansion considered up to the higher order. To the resulting formal linear system, the LQ control theory is applied to obtain another LQ control. Finally these two-type LQ controls are smoothly united to form a single nonlinear control. Numerical experiments indicate that this control show remarkable performances for a nonlinear system.

Keywords: Formal Linearization, LQ Control, Nonlinear Control, Taylor Expansion, Zero Function.

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Authors: Shuhua Lai, Kairui Chen

Abstract:

In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.

Keywords: Coarsening, mesh clustering, shape approximation, mesh simplification.

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Authors: S. Bangphan, P. Bangphan, T. Boonkang

Abstract:

Quality control helps industries in improvements of its product quality and productivity. Statistical Process Control (SPC) is one of the tools to control the quality of products that turning practice in bringing a department of industrial engineering process under control. In this research, the process control of a turning manufactured at workshops machines. The varying measurements have been recorded for a number of samples of a rice polished cylinder obtained from a number of trials with the turning practice. SPC technique has been adopted by the process is finally brought under control and process capability is improved.

Keywords: Rice polished cylinder, statistical process control, control charts, process capability.

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Authors: C. Rajan, K. Geetha, C. Rasi Priya, R. Sasikala

Abstract:

Nature is a great source of inspiration for solving complex problems in networks. It helps to find the optimal solution. Metaheuristic algorithm is one of the nature-inspired algorithm which helps in solving routing problem in networks. The dynamic features, changing of topology frequently and limited bandwidth make the routing, challenging in MANET. Implementation of appropriate routing algorithms leads to the efficient transmission of data in mobile ad hoc networks. The algorithms that are inspired by the principles of naturally-distributed/collective behavior of social colonies have shown excellence in dealing with complex optimization problems. Thus some of the bio-inspired metaheuristic algorithms help to increase the efficiency of routing in ad hoc networks. This survey work presents the overview of bio-inspired metaheuristic algorithms which support the efficiency of routing in mobile ad hoc networks.

Keywords: Ant colony optimization algorithm, Genetic algorithm, naturally inspired algorithms and particle swarm optimization algorithm.

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Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

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Authors: K. Geetha, P. Thangaraj, C. Rasi Priya, C. Rajan, S. Geetha

Abstract:

This paper presents the performance of Integrated Bacterial Foraging Optimization and Particle Swarm Optimization (IBFO_PSO) technique in MANET routing. The BFO is a bio-inspired algorithm, which simulates the foraging behavior of bacteria. It is effectively applied in improving the routing performance in MANET. In results, it is proved that the PSO integrated with BFO reduces routing delay, energy consumption and communication overhead.

Keywords: Ant Colony Optimization, Bacterial Foraging Optimization, Hybrid Routing Intelligent Algorithm, Naturally inspired algorithms, Particle Swarm Optimization.

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: Model predictive control, optimal control, crystal growth, process control.

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Authors: Gishantha Thantulage, Tatiana Kalganova, Manissa Wilson

Abstract:

Ant Colony Algorithms have been applied to difficult combinatorial optimization problems such as the travelling salesman problem and the quadratic assignment problem. In this paper gridbased and random-based ant colony algorithms are proposed for automatic 3D hose routing and their pros and cons are discussed. The algorithm uses the tessellated format for the obstacles and the generated hoses in order to detect collisions. The representation of obstacles and hoses in the tessellated format greatly helps the algorithm towards handling free-form objects and speeds up computation. The performance of algorithm has been tested on a number of 3D models.

Keywords: Ant colony algorithm, Automatic hose routing, tessellated format, RAPID.

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Authors: F. Soleymani, M. Sharifi

Abstract:

Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which is to some extent like the secant method, is accompanied with some numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically iterative schemes.

Keywords: Non-linear equation, iterative methods, derivative-free, convergence.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

Abstract:

This paper presents design trade-off and performance impacts of the amount of pipeline phase of control path signals in a wormhole-switched network-on-chip (NoC). The numbers of the pipeline phase of the control path vary between two- and one-cycle pipeline phase. The control paths consist of the routing request paths for output selection and the arbitration paths for input selection. Data communications between on-chip routers are implemented synchronously and for quality of service, the inter-router data transports are controlled by using a link-level congestion control to avoid lose of data because of an overflow. The trade-off between the area (logic cell area) and the performance (bandwidth gain) of two proposed NoC router microarchitectures are presented in this paper. The performance evaluation is made by using a traffic scenario with different number of workloads under 2D mesh NoC topology using a static routing algorithm. By using a 130-nm CMOS standard-cell technology, our NoC routers can be clocked at 1 GHz, resulting in a high speed network link and high router bandwidth capacity of about 320 Gbit/s. Based on our experiments, the amount of control path pipeline stages gives more significant impact on the NoC performance than the impact on the logic area of the NoC router.

Keywords: Network-on-Chip, Synchronous Parallel Pipeline, Router Architecture, Wormhole Switching

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Authors: M. Faraji, F. Berroug

Abstract:

A one-dimensional mathematical model was developed in order to analyze and optimize the latent heat storage wall. The governing equations for energy transport were developed by using the enthalpy method and discretized with volume control scheme. The resulting algebraic equations were next solved iteratively by using TDMA algorithm. A series of numerical investigations were conducted in order to examine the effects of the thickness of the PCM layer on the thermal behavior of the proposed heating system. Results are obtained for thermal gain and temperature fluctuation. The charging discharging process was also presented and analyzed.

Keywords: Phase change material, Building, Concrete, Latent heat, Thermal control.

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Authors: Z. Pooranian, A. Harounabadi, M. Shojafar, N. Hedayat

Abstract:

The purpose of Grid computing is to utilize computational power of idle resources which are distributed in different areas. Given the grid dynamism and its decentralize resources, there is a need for an efficient scheduler for scheduling applications. Since task scheduling includes in the NP-hard problems various researches have focused on invented algorithms especially the genetic ones. But since genetic is an inherent algorithm which searches the problem space globally and does not have the efficiency required for local searching, therefore, its combination with local searching algorithms can compensate for this shortcomings. The aim of this paper is to combine the genetic algorithm and GELS (GAGELS) as a method to solve scheduling problem by which simultaneously pay attention to two factors of time and number of missed tasks. Results show that the proposed algorithm can decrease makespan while minimizing the number of missed tasks compared with the traditional methods.

Keywords: Grid Computing, Genetic Algorithm, Gravitational Emulation Local Search (GELS), missed task

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Authors: S. Swain, P. S Khuntia

Abstract:

In this paper, the unstable angle of attack of a FOXTROT aircraft is controlled by using Genetic Algorithm based flight controller and the result is compared with the conventional techniques like Tyreus-Luyben (TL), Ziegler-Nichols (ZN) and Interpolation Rule (IR) for tuning the PID controller. In addition, the performance indices like Mean Square Error (MSE), Integral Square Error (ISE), and Integral Absolute Time Error (IATE) etc. are improved by using Genetic Algorithm. It was established that the error by using GA is very less as compared to the conventional techniques thereby improving the performance indices of the dynamic system.

Keywords: Angle of Attack, Genetic Algorithm, Performance Indices, PID Controller.

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Authors: J. Florescu, T. Vinay, L. Wang

Abstract:

A fault detection and identification (FDI) technique is presented to create a fault tolerant control system (FTC). The fault detection is achieved by monitoring the position of the light source using an array of light sensors. When a decision is made about the presence of a fault an identification process is initiated to locate the faulty component and reconfigure the controller signals. The signals provided by the sensors are predictable; therefore the existence of a fault is easily identified. Identification of the faulty sensor is based on the dynamics of the frame. The technique is not restricted to a particular type of controllers and the results show consistency.

Keywords: algorithm, detection and diagnostic, fault-tolerantcontrol, fault detection and identification.

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Authors: Ben Muenzberg, Prof. Peter Nyhuis

Abstract:

The logistical requirements placed on industrial manufacturing companies are steadily increasing. In order to meet those requirements, a consistent and efficient concept is necessary for production control. Set up properly, production control offers considerable potential with respect to achieving the logistical targets. As experience with the many production control methods already in existence and their compatibility is, however, often inadequate, this article describes a systematic approach to the configuration of production control based on the Lödding model. This model enables production control to be set up individually to suit a company and the requirements. It therefore permits today-s demands regarding logistical performance to be met.

Keywords: Production, planning, control, configuration.

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Authors: Ahmad M. Awwad, Jehad Al-Sadi

Abstract:

The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: Interconnection networks, Load balancing, Star network.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Ahmad Darabi, Hassan Moradi, Hossein Azarinfar

Abstract:

In this paper presented initial design of Low Speed Axial Flux Permanent Magnet (AFPM) Machine with Non-Slotted TORUS topology type by use of certain algorithm (Appendix). Validation of design algorithm studied by means of selected data of an initial prototype machine. Analytically design calculation carried out by means of design algorithm and obtained results compared with results of Finite Element Method (FEM).

Keywords: Axial Flux Permanent Magnet (AFPM) Machine, Design Algorithm, Finite Element Method (FEM), TORUS

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

Abstract:

Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.

Keywords: Gradient descent method, jacobian matrix.Levenberg-Marquardt algorithm, quadratic error surfaces,

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Authors: Tao Zhao, Xin Wang

Abstract:

With the increasing complexity of engineering problems, the traditional, single-objective and deterministic optimization method can not meet people-s requirements. A multi-objective fuzzy optimization model of resource input is built for M chlor-alkali chemical eco-industrial park in this paper. First, the model is changed into the form that can be solved by genetic algorithm using fuzzy theory. And then, a fitness function is constructed for genetic algorithm. Finally, a numerical example is presented to show that the method compared with traditional single-objective optimization method is more practical and efficient.

Keywords: Fitness function, genetic algorithm, multi-objectivefuzzy optimization, satisfaction degree membership function.

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Authors: Yash Pal, A.Swarup, Bhim Singh

Abstract:

This paper presents a novel control strategy of a threephase four-wire Unified Power Quality (UPQC) for an improvement in power quality. The UPQC is realized by integration of series and shunt active power filters (APFs) sharing a common dc bus capacitor. The shunt APF is realized using a thee-phase, four leg voltage source inverter (VSI) and the series APF is realized using a three-phase, three leg VSI. A control technique based on unit vector template technique (UTT) is used to get the reference signals for series APF, while instantaneous sequence component theory (ISCT) is used for the control of Shunt APF. The performance of the implemented control algorithm is evaluated in terms of power-factor correction, load balancing, neutral source current mitigation and mitigation of voltage and current harmonics, voltage sag and swell in a three-phase four-wire distribution system for different combination of linear and non-linear loads. In this proposed control scheme of UPQC, the current/voltage control is applied over the fundamental supply currents/voltages instead of fast changing APFs currents/voltages, there by reducing the computational delay and the required sensors. MATLAB/Simulink based simulations are obtained, which support the functionality of the UPQC. MATLAB/Simulink based simulations are obtained, which support the functionality of the UPQC.

Keywords: Power Quality, UPQC, Harmonics, Load Balancing, Power Factor Correction, voltage harmonic mitigation, currentharmonic mitigation, voltage sag, swell

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Authors: Binu Thomas, Raju G., Sonam Wangmo

Abstract:

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algorithm and its extensions, we propose a modification to the cmeans algorithm to overcome the limitations of it in calculating the new cluster centers and in finding the membership values with natural data. The efficiency of the new modified method is demonstrated on real data collected for Bhutan-s Gross National Happiness (GNH) program.

Keywords: Adaptive fuzzy clustering, clustering, fuzzy logic, fuzzy clustering, c-means.

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Authors: S. Raja Balachandar, K.Kannan

Abstract:

A new Meta heuristic approach called "Randomized gravitational emulation search algorithm (RGES)" for solving vertex covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters -velocity- and -gravity- in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility specifically for the vertex covering problem to yield best solutions. The performance of this algorithm has been evaluated on a large set of benchmark problems from OR-library. Computational results showed that the randomized gravitational emulation search algorithm - based heuristic is capable of producing high quality solutions. The performance of this heuristic when compared with other existing heuristic algorithms is found to be excellent in terms of solution quality.

Keywords: Vertex covering Problem, Velocity, Gravitational Force, Newton's Law, Meta Heuristic, Combinatorial optimization.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Inderpreet Kaur, Birinderjit S. Kalyan

Abstract:

This work is a proposed model of CMOS for which the algorithm has been created and then the performance evaluation of this proposition has been done. In this context, another commonly used model called ZSTT (Zero Switching Time Transient) model is chosen to compare all the vital features and the results for the Proposed Equivalent CMOS are promising. In the end, the excerpts of the created algorithm are also included

Keywords: Dual Capacitor Model, ZSTT, CMOS, SPICEMacro-Model.

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Authors: Leehter Yao, Kuei-Song Weng, Cherng-Dir Huang

Abstract:

A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.

Keywords: Ellipsoids, genetic algorithm, classification, fuzzyc-means (FCM)

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Authors: Mustafa Resa Becan

Abstract:

Sliding mode control with a fuzzy boundary layer is presented to hydraulic position control problem in this paper. A nonlinear hydraulic servomechanism which has an asymmetric cylinder is modeled and simulated first, then the proposed control scheme is applied to this model versus the conventional sliding mode control. Simulation results proved that the chattering free position control is achieved by tuning the fuzzy scaling factors properly.

Keywords: Hydraulic servomechanism, position control, sliding mode control, chattering, fuzzy boundary layer.

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