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  • PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter
    1-7.
    Views:
    630

    This paper is focused on the dynamic of mathematical modeling, stability, nonlinear gain control by using Genetic algorithm, utilizing MATLAB tool of a quadcopter. Previously many researchers have been work on several linear controllers such as LQ method; sliding mode and classical PID are used to stabilize the Linear Model. Quadcopter has a nonlinear dynamics and unstable system. In order to maintain their stability, we use nonlinear gain controllers; classical PID controller provides linear gain controller rather than nonlinear gain controller; here we are using modified PID control to improve stability and accuracy. The stability is the state of being resistant to any change. The task is to maintain the quadcopter stability by improving the performance of a PID controller in
    term of time domain specification. The goal of PID controller design is to determine a set of gains: Kp, Ki, and Kd, so as to improve the transient response and steady state response of a system as: by reducing the overshoot; by shortening the settling time; by decrease the rise time of the system. Modified PID is the combination of classical PID in addition to Genetic Algorithm. Genetic algorithm consists of three steps: selection, crossover, and mutation. By using Genetic algorithm we correct the behavior of quadcopter.

  • Modelling and Simulation of Stepper Motor For Position Control Using LabVIEW
    1-5.
    Views:
    1590

    This paper presents hybrid stepper motor (is a type of stepping motor) modelling and simulation which is widely used a kind of motor in industrial applications. In this study, the stepper motor was modelled using bond graph technique and simulation for desired position was executed on LabVIEW
    graphical interface. Then, firstly a convenient PID controller was designed for position, speed and current and PID close loopresponse was obtained for position control. Then, PID parameters for each controller were arranged separately to obtain good response Secondly, Fuzzy Logic controller applied to
    the system and its response was obtained. Finally, both responses are compared. According to comparison, it was observed that Fuzzy Logic controller’s response is better than PID’s. (In this paper, all shown responses were observed for 120 degree desired position)

  • Trajectory Control of Designed Experimental Mobile Robot
    1-5.
    Views:
    255

    Due to advancing technology; nowadays mobile robot applications in hospitals have been increased. For that reason, it is very important and necessary to analyze the trajectory of such helping robotic system. However; there are many types of mobile robots have been utilized in hospital applications such as helping nurses. In this simulation study; a designed and controlled mobile robot was controlled by using standard feedback controllers. On the other hand, the robot was also tested with disturbances of ground surface roughness. The simulation results were improved that standard PID controller has superior performance to overcome surface roughness of the robot trajectory.

  • Sway Control of 3-Cars Crane System Using Proposed Fuzzy-PID Controller
    1-8.
    Views:
    224

    This paper presents a novel control approach for 3 cars crane systems. Nowadays; some problems for carrying unpredicted loads of crane systems exist. On the other hand; long bar loads are very important to carry without touch on other materials in factories. In this simulation study, fuzzy based controllers were designed to control vibrations of 3 cars crane system. The simulation results are improved and show this kind of controllers will be employed in real time such systems.

  • Speed Control of Three Phase Induction Motor Using Scalar Method and PID Controller
    1-5.
    Views:
    194

    This paper presents the speed control of a three-phase induction motor using the scalar control method with PID controller. The system maintains a constant volt to frequency ratio for any change in the load. We also used vector control method and bond graph to describe the motor model, as well as its behavior. Finally, we simulated the system using Labview, where the good results of using the scalar control technique are shown.

  • Brushless DC Motor Modeling Using Bond Graph Method and Control using LabVIEW: Speed control based calssical PID control
    1-5.
    Views:
    242

    This paper aims to simulate and control a three-phase Brushless DC Motor. Bond Graph method has been used to obtain fast and simple dynamic model. The system has been controlled by classical PID controller. All the paper results were fulfilled using LabVIEW program.

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