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This paper presents the inverted PID control of a quadrotor based on the experimentally measured sensors and actuators’ specifications. The main goal is the control and closed loop simulation of a quadrotor using inverted PID algorithm. First, a nonlinear model of quadrotor is derived using Newton-Euler equations. To have a more realistic simulation a setup were designed and developed to measure the sensors noise performance as well as the actuators’ dynamics. The setup involves a platform that two brushless motors mounted at the ends and rotates on a shaft. The platform attitude is measured using the MEMS sensors attached to it. A Kalman filter was used to reduce the sensors noises effect. Results demonstrate good performance for Kalman filter and the controller.

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The Stewart platform with six degree of freedom (three translational and three rotational motions) consists of two rigid bodies, lower plate (base) and upper one (mobile). These two bodies are connected together by six extensible legs between three pairs of joints on each of the bodies. This platform can be used to isolate the top plate of the platform and its payload from the applied motions to the base. Since the passive isolation methods are not effective in elimination of the high amplitude (and usually) low frequency motions, this paper practically investigates the possibility of using the 6DOF Stewart platform as an active vibration isolator. In this study, a Stewart platform was designed and constructed based on electric actuators (servo-motors). And then it was practically utilized to isolate its top plate from the applied pitch and roll rotations to the base plate. MEMS sensors including two accelerometers and one rate gyro along with Kalman filter and kinematic relations were utilized for measuring the pitch and roll motions. A PI controller was implemented to keep the top plate at level position using the MEMS sensors installed on the bottom plate. The experimental results indicated that the platform can effectively isolate the pitch and roll motions while the frequency of these motions is in the working speed range of the electric actuators.

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This paper presents the control of a quadrotor using nonlinear approaches based on the experimentally measured sensors data. The main goal is the control and closed loop simulation of a quadrotor using feedback linearization and sliding mode algorithms. First, a nonlinear model of quadrotor is derived using Newton-Euler equations. To have a more realistic simulation the sensors noise performance were measured using a setup. sensors data was measured under on engines. Since the experimental data for sensor had error and noise, a Kalman filter was used to reduce sensors noise effect. Results demonstrate good performance for Kalman filter and controllers. Results showed that feedback linearization and sliding mode controllers performance was good but angles changes were smoother on feedback linearization controller. With increasing uncertainty, feedback linearization performance was away desired mode from this aspect The time to reach the goal situation while increasing uncertainty was no significant impact on the performance of sliding mode controller.Thus feedback linearization controller added PID is Appropriate to Maintain the quadrotor attitude while sliding mode controller has better performance to angles change and transient situations.

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The purpose of this article is dynamic modeling of a quadrotor and control of its Roll and Pitch angles based on the experimentally measured sensors data. So, after driving nonlinear model of quadrotor equations, the control of the quadrotor’s angular situation was simulated using PID and feedback linearization algorithms. Due to the widespread application of MEMS sensors in measuring the status of various systems and to have a more realistic simulation, sensors data was measured and used in simulation of controllers. Due to errors of MEMS sensors, vibration of motors and airframe, being noise on outputs, Kalman filter was used for estimation of angular situation. As one of the purposes of this paper was the use of its results in actual control of a quadrotor, motor model was used to determine PWM control signals. The results obtained from simulation in Simulink showed good performance of both controllers in controlling roll and pitch angles.