Quadrotor trajectory tracking using PID cascade control

Abstract

Quadrotors have been applied to collect information for traffic, weather monitoring, surveillance and aerial photography. In order to accomplish their mission, quadrotors have to follow specific trajectories. This paper presents proportional-integral-derivative (PID) cascade control of a quadrotor for path tracking problem when velocity and acceleration are small. It is based on near hover controller for small attitude angles. The integral of time-weighted absolute error (ITAE) criterion is used to determine the PID gains as a function of quadrotor modeling parameters. The controller is evaluated in three-dimensional environment in Simulink. Overall, the tracking performance is found to be excellent for small velocity condition. IntroductionRecently, a growing interest in unmanned aerial vehicles (UAVs) has been shown among the research community. Quadcopters are flying vehicles that can be equipped with cameras and sensors to perform many complex tasks. Due to their high maneuverability and small size, quadrotors have been widely used. Their potential applications include search-and-rescue, homeland security, military surveillance, and earth sciences [1][2][3]. In general, quadrotors are naturally unstable, under-actuated, under damped, coupled and nonlinear systems that need to be controlled. Several control techniques can be utilized to control a quadrotor including proportional-integral-derivative (PID) [4,5], linear quadratic regulator (LQR) [6], and backstepping and sliding mode control [7,8]. Because of its simple structure and good stability, PID plays an important role in quadrotor control.In this study, a PID controller is used for attitude and position control. Assuming small acceleration and small attitude angles, the corresponding control laws are derived. A Simulink model is developed where the performance of the controller is tested for different path-tracking cases.

An Online Adaptive Control Strategy for Trajectory Tracking of Quadrotors Based on Fuzzy Approximation and Robust Sliding Mode Algorithm

“…According to the virtual variables in , , Eq. (3)(4)(5)(6)(7)(8)(9)(10)(11), (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) and (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14), for parameters 1 > 1 , 3 > 2 , 1 > 3 , where 1 , 2 and 3 is the upper bound of disturbance 1 ( , , . ), 2 ( , , .…”

“…(1) Cascade PID controller (PID) [14] (2) Improved sliding mode controller (M-SOSM) [23] (3) Fuzzy sliding mode controller (Fuzzy M-SOSM) (4) Elaborated fuzzy adaptive sliding mode controller (AdapFuzzy M-SOSM)…”

“…∈ [7,8] 1, ∈ [13,14] ( ) = 0.1 According to the literature [3], the parameter cx does not affect the stability of the control system but has a direct relationship with the convergence time. If the parameter cx is too large, the fast convergence speed will produce strong buffeting; if the parameter a is too small, the convergence time will be longer.…”

“…Initially, linear control algorithms such as single loop or multi-loop PID and linear quadratic regulator (LQR) were widely applied to control the quadrotor. This was because they had advantages in both simplicity and practicability [13][14]. These algorithms performed reasonably well when the 2 aircraft worked in actual operating conditions.…”

“…These algorithms performed reasonably well when the 2 aircraft worked in actual operating conditions. For instance, a PID cascade control of the quadrotor for trajectory tracking with small acceleration was proposed in [14]; its tracking performance was shown to be excellent for low velocities. However, the fitting effect and control accuracy of these algorithms for nonlinearities were unsatisfactory.…”