Agile spacecraft attitude control: An incremental nonlinear dynamic inversion approach

This paper presents an agile and robust spacecraft attitude tracking controller using the recently reformulated incremental nonlinear dynamic inversion (INDI). INDI is a combined model- and sensor-based control approach that only requires a control effectiveness model and measurements of the state and some of its derivatives, making a reduced dependency on exact system dynamics knowledge. The reformulated INDI allows a non-cascaded dynamic inversion control in terms of Modified Rodrigues Parameters (MRPs) where scheduling of the time-varying control effectiveness is done analytically. This way, the controller is only sensitive to parametric uncertainty of the augmented spacecraft inertia and its wheelset alignment. Moreover, we draw some parallels to time-delay control (TDC) -more familiar in the robotics community- which have been shown to be equivalent to the incremental formulation of proportional-integral-derivative (PID) control for second order nonlinear systems in controller canonical form. Simulation experiments for this particular problem demonstrate that INDI has similar nominal performance as TDC/PID control, but superior robust performance and stability.Control & Simulatio

Efficient Nonlinear Actuator Fault Reconstruction System

Control & Simulatio

Online safe flight envelope prediction for damaged aircraft: A database-driven approach

harvest AIAA 2016-1189Control & Simulatio

Gust Disturbance Alleviation with Incremental Nonlinear Dynamic Inversion

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. This method was developed for the attitude control of MAVs, but in this paper we generalize this method to the outer loop control of MAVs under gust loads. Significant improvements over a traditional Proportional Integral Derivative (PID) controller are demonstrated in an experiment where the drone flies in and out of a fan's wake. The control method does not rely on frequent position updates, so it is ready to be applied outside with standard GPS modules.Control & Simulatio

Autonomous Navigation in Partially Observable Environments Using Hierarchical Q-Learning

Flapping-wing MAVs represent an attractive alternative to conventional designs with rotary wings, since they promise a much higher efficiency in forward flight. However, further insight into the flapping-wing aerodynamics is still needed to get closer to the flight performance observed in natural fliers. Here we present the first step necessary to perform a flow visualization study of the air around the flapping wings of a DelFly II MAV in-flight: a precision position control of flight in a wind-tunnel. We propose a hierarchical control scheme implemented in the open-source Paparazzi UAV autopilot software. Using a decoupling, combined feed-forward and feed-back control approach as a core, we were able to achieve a precision of 2:5 cm for several seconds, which is much beyond the requirements for a time resolved stereo PIV technique.Control & Simulatio

Adaptive Incremental Nonlinear Dynamic Inversion for Attitude Control of Micro Air Vehicles

Incremental nonlinear dynamic inversion is a sensor-based control approach that promises to provide high-performance nonlinear control without requiring a detailed model of the controlled vehicle. In the context of attitude control of micro air vehicles, incremental nonlinear dynamic inversion only uses a control effectiveness model and uses estimates of the angular accelerations to replace the rest of the model. This paper provides solutions for two major challenges of incremental nonlinear dynamic inversion control: how to deal with measurement and actuator delays, and how to deal with a changing control effectiveness. The main contributions of this article are 1) a proposed method to correctly take into account the delays occurring when deriving angular accelerations from angular rate measurements; 2) the introduction of adaptive incremental nonlinear dynamic inversion, which can estimate the control effectiveness online, eliminating the need for manual parameter estimation or tuning; and 3) the incorporation of the momentum of the propellers in the controller. This controller is suitable for vehicles that experience a different control effectiveness across their flight envelope. Furthermore, this approach requires only very coarse knowledge of model parameters in advance. Real-world experiments show the high performance, disturbance rejection, and adaptiveness properties.Control & Simulatio

Comparison of three control structures for inducing higher-order sliding modes

For mitigating the chattering effect in the sliding mode control (SMC), many adaption mechanisms have been proposed to reduce the switching gains. However, less attention is paid to the control structure, which influences the resulting uncertainty term and determines the minimum possible gains. This paper compares three control structures for inducing higher-order sliding modes in finite time: nonlinear dynamic inversion (NDI) based SMC, higher-order sliding mode control (HOSMC) with artificially increased relative degree, and the recently proposed incremental nonlinear dynamic inversion (INDI) based SMC. The latter two control structures have reduced model dependency as compared to NDI-SMC. Moreover, their nominal control increments are found to be approximately equivalent if the sampling interval is sufficiently small and if their gains satisfy certain conditions. Under the same circumstances, the norm value of the resulting uncertainty using INDI-SMC is several orders of magnitude smaller than those using other control structures. For maintaining the sliding modes, the minimum possible gains required by HOSMC approximately equal those needed by INDI-SMC divided by the sampling interval. Nevertheless, these two approaches have comparable chattering degrees, which are effectively reduced as compared to NDI-SMC. The analytical results are verified by numerical simulations.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Control & SimulationAerospace Structures & Computational Mechanic

Quadrotor fault-tolerant incremental nonsingular terminal sliding mode control

This paper proposes incremental nonsingular terminal sliding mode control for a class of multi-input and multi-output nonlinear systems considering model uncertainties, external disturbances, and sudden actuator faults. This method is free from singularity because it does not involve any negative fractional power. The convergence time in both reaching and sliding phases are proved to be finite. Moreover, by fully exploiting sensor measurements, the proposed incremental control method simultaneously reduces model dependency and the uncertainty remaining in the closed-loop system. The reduction of model dependency simplifies the implementation process and reduces the computational load, while the reduction of uncertainty decreases the minimum possible sliding mode control gains, which is beneficial to chattering reduction. These merits are verified by a quadrotor trajectory tracking problem. Simulation results demonstrate that the proposed method has better robustness against model uncertainties, gusts, and actuator faults than the model-based nonsingular terminal sliding mode control in the literature.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Control & Simulatio

Distance and velocity estimation using optical flow from a monocular camera

Monocular vision is increasingly used in micro air vehicles for navigation. In particular, optical flow, inspired by flying insects, is used to perceive vehicle movement with respect to the surroundings or sense changes in the environment. However, optical flow does not directly provide us the distance to an object or velocity, but the ratio of them. Thus, using optical flow in control involves nonlinearity problems which add complexity to the controller. To deal with that, we propose an algorithm that estimates distance and velocity of the vehicle based on optical flow measured from a monocular camera and the knowledge of control inputs. This algorithm applies an extended Kalman filter to state estimation and uses the estimates for landing control. We implement and test our algorithm in computer simulation and on board a Parrot AR.Drone 2.0 to demonstrate its feasibility for micro air vehicles landings. Results of the simulation and multiple flight tests show that the algorithm is able to estimate height and velocity of the micro air vehicles accurately, and achieves smooth landings with these estimates, even in windy outdoor environments.Control & Simulatio

Adaptive spacecraft attitude control with incremental approximate dynamic programming

This paper presents an adaptive control technique to deal with spacecraft attitude tracking and disturbance rejection problems in the presence of model uncertainties. Approximate dynamic programming has been proposed to solve adaptive, optimal control problems without using accurate systems models. Within this category, linear approximate dynamic programming systematically utilizes a quadratic cost-to-go function and simplifies the design process. Although modelfree and efficient, linear approximate dynamic programming methods are difficult to apply to nonlinear systems or timevarying systems, such as attitude control of spacecraft disturbed by internal liquid sloshing. To deal with this problem, this paper develops a model-free nonlinear self-learning attitude control method based on incremental Approximate Dynamic Programming to enhance the performance of the spacecraft attitude control system. This method combines the advantages of linear approximate dynamic programming and the incremental nonlinear control techniques, and generates a model-free controller for unknown, time-varying dynamical systems. In this paper, two reference tracking algorithms are developed for off-line learning and online learning, respectively. These algorithms are applied to the attitude control of a spacecraft disturbed by internal liquid sloshing. The results demonstrate that the proposed method deals with the unknown, timevarying internal dynamics adaptively while retaining accurate and efficient attitude control.Control & Simulatio