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• PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter

  1-7.

  Komal Khuwaja

  Noor-u-Zaman Lighari

  Ioan Constantin Tarca

  Radu Catalin Tarca

  Views:

  692

  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.

• Adaptive Backstepping Controller of PMLSM

  1-6.

  Maamar Yahiaoui

  I. Kh. Bousserhane

  Y. Saidi

  M. Serraoui

  Views:

  264

  In this paper, a nonlinear adaptive speed controller for permanent magnet linear synchronous motors based on a newly developed adaptive recursive Backstepping control approach for a permanent magnet synchronous motor drive is discussed and analyzed. The Backstepping technique provides a systematic method to address this type of problem. It combines the notion of Lyapunov function and a controller procedure recursively.  The adaptive Backstepping control approach is utilized to obtain the robustness for mismatched parameter uncertainties. The overall stability of the system is shown using Lyapunov stability theorem. The simulation results clearly show that the proposed scheme can track the speed reference.

• Aspects Regarding Fly Control of Quadcopter

  1-5.

  Endrowednes Kuantama

  Ioan Tarca

  Radu Tarca

  Dan Craciun

  Views:

  138

  Quadcopter is one of Unmanned Aerial Vehicle (UAV) which has two pairs of identical fixed pitched rotor propellers. It can fly autonomously based on pre-programmed flight or manually controlled by a remote, and every movement achieved by varying the speed of each rotor independently. The orientation of quadcopter axes relative to a reference line and its direction of motion are known as attitude. Fly control factors are affected by attitude determination which can be calculated from 3 possible angles using combined measurement. Gyroscope and accelerometer are primary sensors to control quadcopter attitude, but magnetometer sensor and GPS also used to enhance the stability during flight. This paper will focus on details of function and mathematical formula of every factor regarding fly control and comparative data of 2 types of orientation sensor used in this system.

• Trajectory Control of Designed Experimental Mobile Robot

  1-5.

  Şahin Yildirim

  Berkay Eren

  Views:

  275

  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.