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Tingting Bai; Daobo Wang. Cooperative trajectory optimization for unmanned aerial vehicles in a combat environment. Science China Information Sciences 2018, 62, 10205 .
AMA StyleTingting Bai, Daobo Wang. Cooperative trajectory optimization for unmanned aerial vehicles in a combat environment. Science China Information Sciences. 2018; 62 (1):10205.
Chicago/Turabian StyleTingting Bai; Daobo Wang. 2018. "Cooperative trajectory optimization for unmanned aerial vehicles in a combat environment." Science China Information Sciences 62, no. 1: 10205.
In this article, a novel hybrid control scheme is proposed for controlling the position of a three-phase brushless direct current (BLDC) motor. The hybrid controller consists of discrete time sliding mode control (SMC) with model free adaptive control (MFAC) to make a new data-driven control (DDC) strategy that is able to reduce the simulation time and complexity of a nonlinear system. The proposed hybrid algorithm is also suitable for controlling the speed variations of a BLDC motor, and is also applicable for the real time simulation of platforms such as a gimbal platform. The DDC method does not require any system model because it depends on data collected by the system about its Inputs/Outputs (IOS). However, the model-based control (MBC) method is difficult to apply from a practical point of view and is time-consuming because we need to linearize the system model. The above proposed method is verified by multiple simulations using MATLAB Simulink. It shows that the proposed controller has better performance, more precise tracking, and greater robustness compared with the classical proportional integral derivative (PID) controller, MFAC, and model free learning adaptive control (MFLAC).
Rana Javed Masood; Dao Bo Wang; Zain Anwar Ali; Babar Khan. DDC Control Techniques for Three-Phase BLDC Motor Position Control. Algorithms 2017, 10, 110 .
AMA StyleRana Javed Masood, Dao Bo Wang, Zain Anwar Ali, Babar Khan. DDC Control Techniques for Three-Phase BLDC Motor Position Control. Algorithms. 2017; 10 (4):110.
Chicago/Turabian StyleRana Javed Masood; Dao Bo Wang; Zain Anwar Ali; Babar Khan. 2017. "DDC Control Techniques for Three-Phase BLDC Motor Position Control." Algorithms 10, no. 4: 110.
In this paper, a novel Model Reference Adaptive Control (MRAC)-based hybrid control algorithm is presented for the trajectory tracking of a tri-rotor Unmanned Aerial Vehicle (UAV). The mathematical model of the tri-rotor is based on the Newton–Euler formula, whereas the MRAC-based hybrid controller consists of Fuzzy Proportional Integral Derivative (F-PID) and Fuzzy Proportional Derivative (F-PD) controllers. MRAC is used as the main controller for the dynamics, while the parameters of the adaptive controller are fine-tuned by the F-PD controller for the altitude control subsystem and the F-PID controller for the attitude control subsystem of the UAV. The stability of the system is ensured and proven by Lyapunov stability analysis. The proposed control algorithm is tested and verified using computer simulations for the trajectory tracking of the desired path as an input. The effectiveness of our proposed algorithm is compared with F-PID and the Fuzzy Logic Controller (FLC). Our proposed controller exhibits much less steady state error, quick error convergence in the presence of disturbance or noise, and model uncertainties.
Zain Anwar Ali; Daobo Wang; Muhammad Aamir; Suhaib Masroor. Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm. Aerospace 2017, 4, 3 .
AMA StyleZain Anwar Ali, Daobo Wang, Muhammad Aamir, Suhaib Masroor. Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm. Aerospace. 2017; 4 (1):3.
Chicago/Turabian StyleZain Anwar Ali; Daobo Wang; Muhammad Aamir; Suhaib Masroor. 2017. "Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm." Aerospace 4, no. 1: 3.
In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.
Zain Anwar Ali; Daobo Wang; Muhammad Aamir. Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV. Sensors 2016, 16, 652 .
AMA StyleZain Anwar Ali, Daobo Wang, Muhammad Aamir. Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV. Sensors. 2016; 16 (5):652.
Chicago/Turabian StyleZain Anwar Ali; Daobo Wang; Muhammad Aamir. 2016. "Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV." Sensors 16, no. 5: 652.
In order to increase the lift force of the unmanned aerial vehicles (UAV) in plateau areas, the UAV is commonly equipped with high span chord ratio wings. However, it may decrease the maneuverability of the aircraft, and thus increasing the risk of flight in complex terrain regions. Thrust vector control is a direct force flight control technique, which enhances the maneuverability and introduces the residual of the flight control system. In this paper, we develop a novel variable thrust direction mechanism, which provides the normal propeller UAV with the capability of directional force control. We propose a combinational flight control strategy for the newly developed UAV. Simulations and real flight test demonstrate the performance of the proposed technique in increasing the maneuverability of the conventional propeller UAV.
Yin Wang; Daobo Wang. Variable thrust directional control technique for plateau unmanned aerial vehicles. Science China Information Sciences 2016, 59, 1 -4.
AMA StyleYin Wang, Daobo Wang. Variable thrust directional control technique for plateau unmanned aerial vehicles. Science China Information Sciences. 2016; 59 (3):1-4.
Chicago/Turabian StyleYin Wang; Daobo Wang. 2016. "Variable thrust directional control technique for plateau unmanned aerial vehicles." Science China Information Sciences 59, no. 3: 1-4.
In this paper a nonlinear model of an underactuated quad rotor aerial robot is derived, based on Newton-Euler formalism, and backstepping based PID control strategy is implemented for the derived model. Model derivation comprises determining equations of motion of the quad rotor in three dimensions and seeking to approximate actuation forces through modeling of aerodynamic coefficients and electric motor dynamics. The derived MIMO model, constituted of translational and rotational subsystem, is dynamically unstable. A nonlinear control strategy is therefore implemented for the quad rotor aerial robot. The control strategy includes integral backstepping control for the translational subsystem and backstepping based PID control for the rotational subsystem. The stability of the control design is ensured by Lyapunov stability theorem. The performance of the nonlinear control strategy is evaluated using nonlinear simulation. The simulation results, obtained from backstepping based PID, are compared with conventional optimized PID controller. For the conventional PID controller, the optimization algorithm used is to minimize the Integral of Absolute Error (IAE). Results of comparison validate effectiveness of the backstepping based PID control strategy for the underactuated aerial robot near quasi stationary flight.
Ashfaq Ahmad Mian; Mian Ilyas Ahmad; Daobo Wang. Backstepping based PID Control Strategy for an Underactuated Aerial Robot. IFAC Proceedings Volumes 2008, 41, 15636 -15641.
AMA StyleAshfaq Ahmad Mian, Mian Ilyas Ahmad, Daobo Wang. Backstepping based PID Control Strategy for an Underactuated Aerial Robot. IFAC Proceedings Volumes. 2008; 41 (2):15636-15641.
Chicago/Turabian StyleAshfaq Ahmad Mian; Mian Ilyas Ahmad; Daobo Wang. 2008. "Backstepping based PID Control Strategy for an Underactuated Aerial Robot." IFAC Proceedings Volumes 41, no. 2: 15636-15641.