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    Alireza Najafiyanfar

    In this paper, a control algorithm based on the Lyapunov stability theory and neural network adaptive scheme is proposed to efficiently regulate the position, attitude, and altitude of a quadrotor through a nonlinear dynamic model. Based... more
    In this paper, a control algorithm based on the Lyapunov stability theory and neural network adaptive scheme is proposed to efficiently regulate the position, attitude, and altitude of a quadrotor through a nonlinear dynamic model. Based on the Lyapunov stability theory, the controller allows the system to continue its task correctly even if one or two rotors of the quadrotor stop working and this is achieved without losing stability. Also, in the presence of parametric uncertainties, the coefficients of the controller are adaptively tuned by the neural network method. The obtained results demonstrated the proper performance of the control algorithm based on different operating conditions and scenarios. In fact, the obtained results demonstrated that the proposed controller exhibits desirable transient behaviour and performance stability. Therefore, for operational purposes where the stability and continuation of the quadrotor mission in case of rotor failure is very important, using the controller proposed in this research is very efficient. The proposed control algorithm is easy to implement, compatible with existing quadrotors, and does not significantly affect the overall energy consumption.
    A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with... more
    A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with a two-loop control structure designed and implemented in it. The inner and faster controller is responsible for adjusting the quadcopter height and angles, and the outer and slower controller is responsible for changing the desired figures of roll and pitch angles to control the system position. Whenever a rotor of the quadcopter rotor fails, the status and position of the system are converged and the system is stabilized. Simulation results based on different scenarios indicate the proper performance of the control system whenever there are external disturbances. Note that the gyroscopic effects because of the propeller rotation were not considered.
    A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with... more
    A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with a two-loop control structure designed and implemented in it. The inner and faster controller is responsible for adjusting the quadcopter height and angles, and the outer and slower controller is responsible for changing the desired figures of roll and pitch angles to control the system position. Whenever a rotor of the quadcopter rotor fails, the status and position of the system are converged and the system is stabilized. Simulation results based on different scenarios indicate the proper performance of the control system whenever there are external disturbances. Note that the gyroscopic effects because of the propeller rotation were not considered.