Yazar "Erkol, Huseyin Oktay" seçeneğine göre listele

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    Attitude controller optimization of four-rotor unmanned air vehicle
    (Sage Publications Ltd, 2018) Erkol, Huseyin Oktay
    Quadrocopters, which are getting much popular day to day, are unmanned air vehicles which have four rotors to fly and maneuver in the air. They are used in military or commercial areas. Researchers are also interested in quadrocopters because their physical structure is simple; they can be modeled linear or nonlinear; and many problems about control, optimization, or artificial intelligence can be studied on it. A stable quadrocopter design requires firstly a good controller design. There are many control methods applied to quadrocopters but the most used one is the PID controller. Every controller needs to be tuned well for a good performance. Optimization algorithms are one of the popular tools for tuning the controllers. They can be used to produce optimum controller parameters with less experiment and in a short time. Each optimization algorithm has a different characteristic and different performance depending on the problem. So a comparison is needed among some popularly used optimization algorithms. In this study, a quadrocopter is modeled, and four PID controllers are designed to control attitude and hover. The optimum parameters for controllers are determined by the artificial bee colony algorithm, particle swarm optimization, and genetic algorithm. Performance of the controllers and optimization algorithms is given comparatively.
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    Linear Quadratic Regulator Design for Position Control of an Inverted Pendulum by Grey Wolf Optimizer
    (Science & Information Sai Organization Ltd, 2018) Erkol, Huseyin Oktay
    In this study, a linear quadratic regulator (LQR) based position controller is designed and optimized for an inverted pendulum system. Two parameters, vertical pendulum angle and horizontal cart position, must be controlled together to move a pendulum to desired position. PID controllers are conventionally used for this purpose and two different PID controllers must be used to move the pendulum. LQR is an alternative method. Angle and position of inverted pendulum can be controlled using only one LQR. Determination of Q and R matrices is the main problem when designing an LQR and they must be minimized a defined performance index. Determination of the Q and R matrices is generally made by trial and error method but finding the optimum parameters using this method is difficult and not guaranty. An optimization algorithm can be used for this purpose and in this way; it is possible to obtain optimum controller parameters and high performance. That's why an optimization method, grey wolf optimizer, is used to tune controller parameters in this study.
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    Optimal PI?D? Controller Design for Two Wheeled Inverted Pendulum
    (Ieee-Inst Electrical Electronics Engineers Inc, 2018) Erkol, Huseyin Oktay
    Fractional order controllers have a growing popularity in last years and they give more flexibility to researchers for designing a controller. In this paper, a fractional order PID controller is designed for the position control of a two wheeled inverted pendulum. The pendulum is modeled with DC electrical motors to obtain a more realistic model. Integer order PID controller is also designed to make a comparison with fractional order controller and all controllers are optimized by swarm algorithms to be sure obtained the best performance for each controller. A fractional order PID controller has two extra parameters (lambda and mu) and totally five parameters to be optimized. Optimization algorithms are powerful tools for designing a controller, and guarantee finding an optimum result. However, each optimization algorithm has a different performance not only because of the structure of the algorithm but also depending on the optimization problem. Because of this, four popular optimization algorithms (artificial bee colony, particle swarm optimization, grey wolf optimizer, and cuckoo search algorithm) are used to tune controller parameters, and compared regard with the optimized system performance. The results show that the best performance is obtained by the fractional order PID controller, which optimized by artificial bee colony algorithm. The fractional order PID controllers have also better performance than integer order PIDs when used the same optimization algorithm for tuning.
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    Optimization and Evaluation of Hybrid PV/WT/BM System in Different Initial Costs and LPSP Conditions
    (Science & Information Sai Organization Ltd, 2017) Tabak, Abdulsamed; Ozkaymak, Mehmet; Guneser, Muhammet Tahir; Erkol, Huseyin Oktay
    A modelling and optimization study was performed to manage energy demand of a faculty in Karabuk University campus area working with a hybrid energy production system by using genetic algorithm (GA). Hybrid system consists of photovoltaic (PV) panels, wind turbines (WT) and biomass (BM) energy production units. Here BM is considered as a back-up generator. Objective function was constituted for minimizing total net present cost (TNPC) in optimization. In order to obtain more accurate results, measurements were performed with a weather station and data were read from an electricity meter. The system was also checked for reliability by the loss of power supply probability (LPSP). Changes in TNPC and localized cost of energy (LCOE) were interpreted by changing LPSP and economic parameters such as PV investment cost, WT investment cost, BM investment cost, and interest rates. As a result, it was seen that a hybrid system consisted of PV and BM associated with an effective flow algorithm benefited from a GA meets the energy demand of the faculty.
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    Optimization of an Inverted Pendulum System by the Artificial Bee Colony Algorithm
    (Gazi Univ, 2017) Erkol, Huseyin Oktay
    In this study, optimization of a Proportional-Integral-Derivative controller for an Inverted Pendulum System was realized by the Artificial Bee Colony algorithm which is becoming widely used. A computer simulation was made to test the optimized system. The simulation results show that the Artificial Bee Colony algorithm is faster and give better results than traditional methods.
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    Optimized Field Oriented Control Design by Multi Objective Optimization
    (Science & Information Sai Organization Ltd, 2019) Erkol, Huseyin Oktay
    Permanent Magnet Synchronous Motors are popular electrical machines in industry because they have high efficiency, low ratio of weight/power and smooth torque with no or less ripple. In addition to this, control of synchronous motor is a complex process. Vector control techniques are widely used for control of synchronous motors because they simplify the control of AC machines. In this study, Field Oriented Control technique is used as a speed controller of a Permanent Magnet Synchronous Motor. The controller must be good tuned for applications which need high performance, and classical methods are not enough or need more time to achieve the requested performance criteria. Optimization algorithms are good options for tuning process of controllers. They guarantee finding one of the best solutions and need less time for solving the problem. Therefore, in this study, Tree-Seed Algorithm is used for tuning process of the controller parameters and the results show that Tree-Seed Algorithm is good tool for controller tuning process. The controller is also tuned by Particle Swarm Algorithm to make a comparison. The results show that optimized system by Tree-Seed Algorithm has good performance for the applications which need changing speed and load torque. It has also better performance than the system which is optimized by Particle Swarm Optimization algorithm.
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    A VHDL application for kinematic equation solutions of multi-degree-of-freedom systems
    (Zhejiang Univ, 2014) Erkol, Huseyin Oktay; Demirel, Huseyin
    As kinematic calculations are complicated, it takes a long time and is difficult to get the desired accurate result with a single processor in real-time motion control of multi-degree-of-freedom (MDOF) systems. Another calculation unit is needed, especially with the increase in the degree of freedom. The main central processing unit (CPU) has additional loads because of numerous motion elements which move independently from each other and their closed-loop controls. The system designed is also complicated because there are many parts and cabling. This paper presents the design and implementation of a hardware that will provide solutions to these problems. It is realized using the Very High Speed Integrated Circuit Hardware Description Language (VHDL) and field-programmable gate array (FPGA). This hardware is designed for a six-legged robot and has been working with servo motors controlled via the serial port. The hardware on FPGA calculates the required joint angles for the feet positions received from the serial port and sends the calculated angels to the servo motors via the serial port. This hardware has a co-processor for the calculation of kinematic equations and can be used together with the equipment that would reduce the electromechanical mess. It is intended to be used as a tool which will accelerate the transition from design to application for robots.