Johann C. Dauer

Optimization-Based Feedforward Path Following for Model Reference Adaptive Control of an Unmanned Helicopter

This paper addresses an optimization based approach to follow a geometrically defined path by an unmanned helicopter. In particular, this approach extends reference model following concepts. Instead of using vehicle dynamics, the optimization is based on the reference model of the controller. This way, we can calculate the time-wise evolution on the path by means of dynamic optimization. The progression on the geometric path, namely the timing law, is defined as a dynamic system subject to an additional virtual control input. The inputs of the reference model and that of the timing law are the decision variables used in the dynamic optimization. It will be shown that this way, an accurate following of the path is possible although the actually identified flight mechanical model is limited to a linear hover model. Furthermore, the approach allows to take constraints on inputs and states into account. Simulation results as well as preliminary flight tests conducted with the ARTIS testbed are presented for two nonlinear and planar paths underlining that good performance and constrains satisfaction can be achieved.

Modular Simulation Framework for Unmanned Aircraft Systems

This paper presents the concept and implementation of a simulation framework, capable of simulating a variety of different kind of unmanned aircraft. The concept is designed for various tests, including software-in-the-loop as well as hardware-in-the-loop simulations. The aim of this framework is to ease the simulation setup for different purposes including algorithm development, software testing and control station design. Different problem abstractions and a desired degree of simulation complexity shall be available. A terminology for this particular problem formulation is proposed. Different layers of configuration are identified and a framework is introduced which allows the automatic simulation setup. A library based approach is presented independent of a development language or tool. Subsequently, an example implementation is introduced within a hybrid Matlab/Simulink and C/C++ environment enabling a fast reuse of simulation modules, like sensors, airframe configurations, and environmental setups. The paper concludes with lessons learned from using this framework during the past years.

Evaluation of Time-Shifted Feedforward Control for Unmanned Helicopter Path Tracking

A novel approach to improve the path tracking performance based on time shifted feed-forward signals is presented. It uses approximately linear closed-loop dynamics through feedback linearization of the ARTIS unmanned helicopter. The flight controller is currently in use to track nonlinear trajectories represented by piece-wise cubic splines. Feedforward signals shifted in time with varying and constant time-shifts are evaluated to improve the suboptimal tracking behavior. The problem is illustrated for a representative path and the process of determining the time shift is discussed. Having runtime performance advantages, the constant variant of time-shifted feedforward signals is chosen for onboard implementation. To validate the approach, it is implemented onboard our flying rotorcraft test bed and flight test results showing the improved tracking performance are presented.

Adaptive Trajectory Controller for Generic Fixed-Wing Unmanned Aircraft

This work deals with the construction of a nonlinear adaptive trajectory controller, which is easily applicable to a multitude of fixed wing unmanned aircraft. Given a common signal interface, the adaptive trajectory controller is divided into a generic part, which is common for each vehicle, and into a part, which is unique. The generic part of the control architecture bases on a common inversion model which is used for feedback linearization. However, the dynamics of the aircraft and the inversion model differ, thus introducing model uncertainties to the feedback linearized system. The effect of modeling uncertainties is reduced by the application of a concurrent learning model reference adaptive controller, which uses neural networks in order to approximate the uncertainty. Leveraging instantaneous as well as stored data concurrently for adaptation ensures convergence of the adaptive parameters to a set of optimal weights, which minimize the approximation error. Performance and robustness against certain model uncertainties is shown through numerical simulation for two significantly different unmanned aircraft.

Run-to-run disturbance rejection for feedforward path following of an adaptively controlled unmanned helicopter

We present a scheme for run-to-run disturbance rejection in optimization-based feedforward path following of a remotely piloted aircraft system (RPAS). The proposed scheme is based on the inter-run estimation of unknown disturbances, such as wind induced forces and model uncertainties. These disturbance estimates are introduced in an optimal control problem used to compute feedforward controls. In order to achieve good run-to-run disturbance rejection, the structure of the underlying stabilizing flight control of the RPAS is taken into account. In this work, we consider flight control based on adaptive reference following and the special case of the unmanned helicopter ARTIS. We present simulation results and flight test data. These results underpin that the proposed approach significantly decreases flight path deviations in a run-to-run fashion.

Steps Towards Scalable and Modularized Flight Software for Unmanned Aircraft Systems

Unmanned aircraft (UA) applications impose a variety of computing tasks on the on-board computer system. From a research perspective, it is often more convenient to evaluate algorithms on bigger aircraft as they are capable of lifting heavier loads and thus more powerful computational units. On the other hand, smaller systems are often less expensive and operation is less restricted in many countries. This paper thus presents a conceptual design for flight software that can be evaluated on the UA of convenient size. The integration effort required to transfer the algorithm to different sized UA is significantly reduced. This scalability is achieved by using exchangeable payload modules and a flexible process distribution on different processing units. The presented approach is discussed using the example of the flight software of a 14 kg unmanned helicopter and an equivalent of 1.5 kg. The proof of concept is shown by means of flight performance in a hardware-in-the-loop simulation.

Computational Aspects of Optimization-Based Path Following of an Unmanned Helicopter

This paper considers the path following of unmanned helicopters based on dynamic optimization. We assume that the helicopter is equipped with a flight control system that provides an approximation of its closed-loop dynamics. The task at hand is to compute inputs for this flight control system in order to track a geometrically specified path. A concise problem formulation and a discussion of an efficient implementation are presented. The implementation achieves computation times below the flight duration of the path by exploiting differential flatness properties of parts of the dynamics. Finally, we present quantitative results with respect to convergence and required iterations for a challenging nonlinear path. We show that the proposed optimization based approach is capable of tackling nonlinear path following for unmanned helicopters in an efficient and practicable manner.

Robustness Analysis of a Formation Flight Guidance Algorithm for Automated Aerial Refueling

This paper considers the formation ight in the context of an automated aerial refueling mission of small-scale aircraft. The attention is concentrated on a simulation-based robustness analysis approach allowing fast re-evaluation of a guidance algorithm, which steers the follower aircraft during the formation ight. The simulation, on which this robustness analysis is based, is easily extendable in order to include gained insight of future experiments. The paper presents results obtained from an exemplarily application of the robustness analysis to a preliminary guidance algorithm of a small unmanned aircraft. The application at this point includes a 3-degree-of-freedom leader aircraft model following an oval racetrack path and a 6-degree-of-freedom follower aircraft model, which is under the e ect of wind.

Considerations of Artificial Intelligence Safety Engineering for Unmanned Aircraft.

Unmanned aircraft systems promise to be useful for a multitude of applications such as cargo transport and disaster recovery. The research on increased autonomous decision-making capabilities is therefore rapidly growing and advancing. However, the safe use, certification, and airspace integration for unmanned aircraft in a broad fashion is still unclear. Standards for development and verification of manned aircraft are either only partially applicable or resulting safety and verification efforts are unrealistic in practice due to the higher level of autonomy required by unmanned aircraft. Machine learning techniques are hard to interpret for a human and their outcome is strongly dependent on the training data. This work presents the current certification practices in unmanned aviation in the context of autonomy and artificial intelligence. Specifically, the recently introduced categories of unmanned aircraft systems and the specific operation risk assessment are described, which provide means for flight permission not solely focusing on the aircraft but also incorporating the target operation. Exemplary, we show how the specific operation risk assessment might be used as an enabler for hard-to-certify techniques by taking the operation into account during system design.

Towards Autonomy and Safety for Unmanned Aircraft Systems

This chapter describes unmanned aircraft with respect to autonomy and safety aspects of aerospace. The focus will be on unmanned aircraft systems, however most of the principles regarding safety and automation are valid for both, manned and unmanned aviation. As a means to assure safety for aircraft, safety assessments, development processes, and software standards have been established for manned aviation. In this context, design-time assurance of software will be discussed. Another key component of the safety concept for manned aviation is the onboard pilot. The pilot supervises and validates the system behavior and develops a gut feeling if the system is okay, due to his onboard presence. This is not possible for an unmanned aircraft. Human supervision will be remotely located. Therefore, an extensive discussion on runtime assurance and automated supervision will be a part of this work. Furthermore, with the growing degrees of automation and upcoming autonomy of the aircraft, one pilot might have to supervise more than one aircraft at the same time. Unmanned aircraft are expected to be integrated into civil airspace in the near future, possibly in very large quantities. The autonomy of these unmanned aircraft and the absence of a pilot onboard the aircraft is a source of concern. However, the automation and autonomy can also support safety. The interdependence between safety and autonomy will be discussed in this chapter. The challenge regarding unmanned aircraft is that the same level of safety can be maintained. In this context, this chapter will discuss the impact of new and upcoming regulations and standards for unmanned aircraft regarding a holistic approach to the assessment of risk and their impact on autonomy and safety.