Cascaded incremental nonlinear dynamic inversion for MAV disturbance rejection

Abstract

Micro Aerial Vehicles (MAVs) are limited in their operation outdoors near obstacles by their ability to withstand wind gusts. Currently widespread position control methods such as Proportional Integral Derivative control do not perform well under the influence of gusts. Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control technique that can control nonlinear systems subject to disturbances. It was developed for the attitude control of manned aircraft or MAVs. In this paper we generalize this method to the outer loop control of MAVs under severe gust loads. Significant improvements over a traditional Proportional Integral Derivative (PID) controller are demonstrated in an experiment where the quadrotor flies in and out of a windtunnel exhaust at 10 m/s. The control method does not rely on frequent position updates, as is demonstrated in an outside experiment using a standard GPS module. Finally, we investigate the effect of using a linearization to calculate thrust vector increments, compared to a nonlinear calculation. The method requires little modeling and is computationally efficient.

Incremental Control and Guidance of Hybrid Aircraft Applied to a Tailsitter Unmanned Air Vehicle

“…Similarly, the attitude can then be controlled by setting a certain reference for the angular rates. A complete derivation and validation of INDI is presented in previous research [20,23] and is beyond the scope of this paper. Here, we will briefly summarize the controller.…”

“…In this paper, we offer a solution to each of the three challenges using only a minimal amount of modelling. For the attitude and velocity control we propose two cascaded Incremental Nonlinear Dynamic Inversion (INDI) controllers, based on our previous work on INDI for quadrotors [20,23]. An INDI controller does not need a model of the vehicle's forces and moments, because these can be derived from the acceleration and angular acceleration respectively.…”

Accurate Tracking of Aggressive Quadrotor Trajectories Using Incremental Nonlinear Dynamic Inversion and Differential Flatness

“…In order to do so, the equation is discretized using finite-difference approximation over the time interval ∆t, resulting in the following relation: which can be solved numerically to obtain the commanded motor speed vector ω c , e.g., using Newton's method. Inversion of this nonlinear control effectiveness relation improves the accuracy of thrust and control moment tracking, when compared to the linearized inversion as shown in [18] (see also (80)). The pulse width modulation vector ζ contains the commands that are sent to the four ESCs, and is obtained as follows:…”

“…State-of-the-art INDI control tracks angular acceleration based on linearization of the control effectiveness equation [17], [18]. We present an INDI implementation based on estimation of the external moment µ ext and nonlinear inversion of (7).…”

Disturbance Estimation and Rejection for High-Precision Multirotor Position Control

“…In [9], a momentum-based estimator of external forces is used in conjunction with an impedance controller. In [10], a Nonlinear Inversion-based position controller uses filtered accelerometer measurements to reconstruct and compensate the acceleration caused by external disturbance, resulting in significant improvement of disturbance rejection. In [11], [12], the external force [11] [12] and torque vectors [11] are estimated using acceleration and velocity measurements.…”