Bin Xian

Nonlinear Robust Adaptive Tracking Control of a Quadrotor UAV Via Immersion and Invariance Methodology

This paper presents a novel asymptotic tracking controller for an underactuated quadrotor unmanned aerial vehicle using the robust integral of the signum of the error (RISE) method and an immersion and invariance (I&I)-based adaptive control methodology. The control system is decoupled into two parts: the inner loop for attitude control and the outer loop for position control. The RISE approach is applied in the inner loop for disturbance rejection, whereas the I&I approach is chosen for the outer loop to compensate for the parametric uncertainties. The asymptotic tracking of the time-varying 3-D position and the yaw motion reference trajectories is proven via the Lyapunov-based stability analysis and LaSalles invariance theorem. Real-time experiment results, which are performed on a hardware-in-the-loop simulation testbed, are presented to illustrate the performance of the proposed control scheme.

Adaptive tracking control of underactuated quadrotor unmanned aerial vehicles via backstepping

This paper considers about the control problem for an underactuated quadrotor UAV system with model parameter uncertainty. Backstepping based techniques are utilized to design a nonlinear adaptive controller which can compensate for the mass uncertainty of the vehicle. Lyapunov based stability analysis shows that the proposed control design yields asymptotic tracking for the UAVs motion in x, y, z direction and the yaw rotation, while keep the stability of the closed loop dynamics of the quadrotor UAV. Numerical simulation results are provided to show the good tracking performance of proposed control laws.

Output feedback control of hypersonic vehicles based on neural network and high gain observer

In this paper, the output feedback control problem for a genetic hypersonic vehicle is considered under the restriction that only the vehicle’s velocity and altitude are measurable. High gain observers (HGO) are utilized to provide estimation signals for unmeasurable derivatives of the vehicle’s velocity and altitude. Neural network based feedforward function is designed to compensate for model uncertainties. The proposed control design require less knowledge of the hypersonic vehicle’s dynamic model. A comprehensive stability analysis of the closed loop system under the output feedback control is carried to prove that the proposed control law yields semiglobal uniformly ultimately bounded tracking while keeping all the closed loop signals bounded. Numerical simulation results are presented to validate the proposed control design.

Autonomous Flight Control of a Nano Quadrotor Helicopter in a GPS-Denied Environment Using On-Board Vision

In this paper, a nano quadrotor helicopter which weighs about only 45 grams and has a diameter less than 0.15 m is employed for the autonomous flight control development in GPS-denied environments. Due to the very limited payload ability of the helicopter, a micro onboard vision system is designed to provide visual pose measurement. Then the attitude data obtained from a low cost micro inertial measurement unit (IMU) are fused with the visual measurement to provide accurate estimation of the helicopters translational position and velocity. Nonlinear flight controller is designed to hold the quadrotor in a certain position and altitude without external ground motion capture system. Moreover, trajectory tracking ability is achieved with the help of a modified visual simultaneous localization and mapping (SLAM) algorithm. Experimental results are included to demonstrate the good hovering and tracking control performance of the proposed design in GPS-denied indoor and outdoor environments. To our best knowledge, few of previous works have demonstrated autonomous control ability of a quadrotor helicopter weighs less than 50 grams without the help of external ground motion capture system in GPS-denied indoor and outdoor environments.

Nonlinear adaptive regulation control of a quadrotor unmanned aerial vehicle

In this paper, a nonlinear adaptive regulation controller is presented for a class of underactuated quadrotor unmanned aerial vehicle (UAV). The vehicles dynamics is subject to modeling impression associated with the inertia matrix, aerodynamic damping coefficients, and some other system parameters. The on-line parameter estimation scheme is combined with feedback control to develop the adaptive control laws. Lyapunov based approaches are utilized to prove that the quadrotor UAVs position and yaw angle regulation errors are ultimately driven to zero under parametric uncertainties. Simulation results are included to demonstrate the performance of the control strategy.

Continuous Robust Tracking Control for Magnetic Levitation System With Unidirectional Input Constraint

In this paper, the exponentially tracking control problem for a magnetic levitation system (MLS) in the presence of parameter uncertainties and external disturbances is investigated. The disturbance/uncertainties-rejecting problem for the MLS is addressed from the view of a continuous nonlinear robust control development. Another problem of the concern is the common unidirectional input constraint in the MLS (i.e., the control input, often referring to the square of the electric current, should be nonnegative during the operation of the system). By utilizing an input transformation and augmented dynamics, a virtual control input, which removes the unidirectional constraint, is affinely emerged in the dynamics. A second-order filter is introduced to provide feedback signals for the control development. A novel Lyapunov function guarantees the exponentially tracking stability of the close-loop dynamics. Finally, some numerical simulation and real-time experimental results for tracking of time-varying trajectories are presented to validate the performance of the proposed control design.

Adaptive backstepping tracking control of a 6-DOF unmanned helicopter

This paper presents an adaptive backstepping control design for a class of unmanned helicopters with parametric uncertainties. The control objective is to let the helicopter track some pre-defined position and yaw trajectories. In order to facilitate the control design, we divide the helicopters dynamic model into three subsystems. The proposed controller combines the backstepping method with online parameter update laws to achieve the control objective. The global asymptotical stability (GAS) of the closed-loop system is proved by a Lyapunov based stability analysis. Numerical simulations demonstrate that the controller can achieve good tracking performance in the presence of parametric uncertainties.

Lyapunov-based adaptive control design for a class of uncertain MIMO nonlinear systems

In this paper, an adaptive feedback control is designed for a class of MIMO nonlinear systems containing parametric uncertainty in both the drift vector and the input gain matrix, which is assumed to be full-rank and non-symmetric in general. Based on an SDU decomposition of the gain matrix, a singularity-free adaptive tracking control law is proposed that is shown to be globally asymptotically stable (GAS) under full-state feedback. Output feedback results are facilitated via the use of a high-gain observer (HGO). Under output feedback control, ultimate boundedness of the error signals is obtained - the size of the bound is related to the size of the uncertainty in the parameters. An explicit upper bound is also provided on the size of the HGO gain constant.

An output feedback attitude tracking controller design for quadrotor unmanned aerial vehicles using quaternion

In this paper, a quaternion based nonlinear output feedback tracking controller is developed to address the attitude and altitude tracking problem of a quadrotor unmanned aerial vehicle (UAV) which is subject to structural uncertainties and unknown external disturbances. A set of filters are introduced to provide estimation for the unmeasurable quadrotor UAVs angular and translational velocity signals. The Lyapunov based stability analysis ensures that a semi-global asymptotic tracking result is achieved and all closed loop states remain bounded with a suitable choice of control gains.

Nonlinear output feedback control design of a hypersonic vehicle via high gain observers

In this paper, the output feedback control problem for a genetic hypersonic vehicle is considered under the restriction that only the vehicles velocity and altitude are measurable. High gain observers (HGO) are utilized to provide estimation signals for unmeasurable derivatives of the vehicles velocity and altitude. A comprehensive stability analysis of the closed loop system under the output feedback control is carried to prove that the proposed control law yields semiglobal uniformly ultimately bounded tracking while keep all the closed loop signals bounded. Numerical simulation results are presented to validate the proposed control design.