Optimization Based Self-localization for IoT Wireless Sensor Networks

In this paper we propose an embedded optimization framework for the simultaneous self-localization of all sensors in wireless sensor networks making use of range measurements from ultra-wideband (UWB) signals. Low-power UWB radios, which provide time-of-arrival measurements with decimeter accuracy over large distances, have been increasingly envisioned for realtime localization of IoT devices in GPS-denied environments and large sensor networks. In this work, we therefore explore different non-linear least-squares optimization problems to formulate the localization task based on UWB range measurements. We solve the resulting optimization problems directly using non-linear-programming algorithms that guarantee convergence to locally optimal solutions. This optimization framework allows the consistent comparison of different optimization methods for sensor localization. We propose and demonstrate the best optimization approach for the self-localization of sensors equipped with off-the-shelf microcontrollers using state-of-the-art code generation techniques for the plug-and-play deployment of the optimal localization algorithm. Numerical results indicate that the proposed approach improves localization accuracy and decreases computation times relative to existing iterative methods

Predictive Control of Autonomous Kites in Tow Test Experiments

In this paper we present a model-based control approach for autonomous flight of kites for wind power generation. Predictive models are considered to compensate for delay in the kite dynamics. We apply Model Predictive Control (MPC), with the objective of guiding the kite to follow a figure-of-eight trajectory, in the outer loop of a two level control cascade. The tracking capabilities of the inner-loop controller depend on the operating conditions and are assessed via a frequency domain robustness analysis. We take the limitations of the inner tracking controller into account by encoding them as optimisation constraints in the outer MPC. The method is validated on a kite system in tow test experiments.Comment: The paper has been accepted for publication in the IEEE Control Systems Letters and is subject to IEEE Control Systems Society copyright. Upon publication, the copy of record will be available at http://ieeexplore.ieee.or

State Estimation for Kite Power Systems with Delayed Sensor Measurements

We present a novel estimation approach for airborne wind energy systems with ground-based control and energy generation. The estimator fuses measurements from an inertial measurement unit attached to a tethered wing and position measurements from a camera as well as line angle sensors in an unscented Kalman filter. We have developed a novel kinematic description for tethered wings to specifically address tether dynamics. The presented approach simultaneously estimates feedback variables for a flight controller as well as model parameters, such as a time-varying delay. We demonstrate the performance of the estimator for experimental flight data and compare it to a state-of-the-art estimator based on inertial measurements

Consistent aeroelastic linearisation and reduced-order modelling in the dynamics of manoeuvring flexible aircraft

This work proposes a novel reduced-order modelling approach in time domain for the coupled flight dynamics and aeroelastic response of manoeuvring very flexible aircraft. The starting point is the coupling of a displacement-based, geometrically-nonlinear flexible-body dynamics formulation with a 3-D unsteady vortex-lattice method. This is followed by a linearisation of the structural degrees of freedom, which are assumed to be small in a body- fixed reference frame. The translations and rotations of that reference frame and their time derivatives, which describe the vehicle flight dynamics, can be arbitrarily large. As a result, all couplings between the rigid and elastic motions are introduced without the a priori assumptions of the mean axes approximation, traditionally used to decouple the equations in flexible-aircraft dynamics. The resulting system can be projected onto a few vibration modes of the unconstrained aircraft with geometrically-nonlinear static deflections at a trim condition. Equally, the unsteady aerodynamics are approximated on a fixed lattice defined by the deformed static geometry. The resulting high-order aerodynamic system, which defines the mapping between the small number of generalised coordinates and unsteady aerodynamic loads, is then reduced through balanced truncation. This unified description of the flexible aircraft dynamics provides a hierarchy of aeroelastic model fidelities, which will be illustrated on a representative high-altitude, long-endurance aircraft to identify the importance of geometrically-nonlinear wing deformations on the vehicle dynamics. Application of the reduced-order modelling approach further shows a very substantial reduction in model size that leads to model orders (and computational cost) similar to those in conventional frequency-based methods but with higher modelling fidelity to compute manoeuvre loads. Closed-loop results for the Goland wing finally demonstrate the application of this approach in the synthesis of a robust flutter suppression controller.Open Acces

Morphing Concept for Multirotor UAVs Enabling Stability Augmentation and Multiple-Parcel Delivery

This paper presents a novel morphing concept for multirotor Unmanned Aerial Vehicles (UAVs) to optimize the vehicle ight performance during multi-parcel deliveries. Abrupt changes in the vehicle weight distribution during a parcel delivery can cause the UAVs to be unbalanced. This is usually compensated by the vehicle ight control system but the motors may need to operate outside their design range which can deteriorate the stability and performance of the system. Morphing the geometry of a conventional multirotor airframe enables the vehicle to continuously re-balanced itself which improves the overall vehicle performance and safety. The paper derives expressions for the static stability of multirotor UAVs and discusses the experimental implementation of the morphing technology on a Y6 tricopter configuration. Flight test results of multi-parcel delivery scenarios demonstrate the capability of the proposed technology to balance the throttle outputs of all rotors

Enabling optimization-based localization for IoT devices

In this paper, we propose an embedded optimization approach for the localization of Internet of Things (IoT) devices making use of range measurements from ultra-wideband (UWB) signals. Low-cost, low-power UWB radios provide time-of-arrival measurements with decimeter accuracy over large distances. UWB-based localization methods have been envisioned to enable feedback control in IoT applications, particularly, in GPS-denied environments, and large wireless sensor networks. In this paper, we formulate the localization task as a nonlinear least-squares optimization problem based on two-way time-of-arrival measurements between the IoT device and several UWB radios installed in a 3-D environment. For the practical implementation of large-scale IoT deployments we further assume only approximate knowledge of the UWB radio locations. We solve the resulting optimization problem directly on IoT devices equipped with off-the-shelf microcontrollers using state-of-the-art code generation techniques for plug-and-play deployment of the nonlinear-programming algorithms. This paper further provides practical implementation details to improve the localization accuracy for feedback control in experimental IoT applications. The experimental results finally show that subdecimeter localization accuracy can be achieved using the proposed optimization-based approach, even when the majority of the UWB radio locations are unknown

Predictive Guidance Control for Autonomous Kites with Input Delay

In this paper we consider the design of a model predictive guidance controller in a cascaded control scheme for an autonomous kite with significant input delay. The input rate of the guidance is bounded to ensure robust performance of the underlying tracking controller. This is achieved by analysisng the limitations of the tracking controller arising from model parameter uncertainty and input delay. The delay is accounted for in the control design by predicting the values of the feedback variables ahead of time based on the past inputs and the system models. To account for changing operating conditions the model parameters are updated online. The proposed method has been tested in a real-time hardware-in-the-loop simulation study

Visual motion tracking and sensor fusion for kite power systems

An estimation approach is presented for kite power systems with groundbased actuation and generation. Line-based estimation of the kite state, including position and heading, limits the achievable cycle efficiency of such airborne wind energy systems due to significant estimation delay and line sag. We propose a filtering scheme to fuse onboard inertial measurements with ground-based line data for ground-based systems in pumping operation. Estimates are computed using an extended Kalman filtering scheme with a sensor-driven kinematic process model which propagates and corrects for inertial sensor biases. We further propose a visual motion tracking approach to extract estimates of the kite position from ground-based video streams. The approach combines accurate object detection with fast motion tracking to ensure long-term object tracking in real time. We present experimental results of the visual motion tracking and inertial sensor fusion on a ground-based kite power system in pumping operation and compare both methods to an existing estimation scheme based on line measurements

Vision-based Navigation for Control of Micro Aerial Vehicles

This paper presents the use of an external vison-based positioning system for navigation and flight control of micro aerial vehicles. The motion capture system Optitrack is used to localize the vehicle which is a nano-quadcopter Crazyflie 2.0. An interface was created to pass positioning data to the Robot Operating Software (ROS). ROS acts as communication layer to bridge between Optitrack and available control nodes for Crazyflie 2.0 platforms

Impact of Unmanned Aircraft Regulations on Autonomous Navigation Approaches for Indoor Multi-Rotor Applications — Survey

Demand in unmanned aircraft (UA) technologies for real-world applications have increased over the recent years, driving national aviation authorities to implement weight dependent regulations across all UA operations. Introduction of registration for UA weighing 250g and above as well as other regulatory requirements for heavier UA systems have motivated manufacturers to consider weight as a part of design requirement. Although UA weight is not a major concern for most outdoor applications, weight requirements imposed by aviation authorities further emphasizes the importance to develop smaller and lighter UA for safer indoor or urban operations in GPS denied environments. Comparison across various sensors used for autonomous UA navigation methods suggested that benefits of using vision sensors outweighs other methods since most UA are equipped with onboard cameras and thus does not require retrofitting of additional hardware. In addition, vision sensor data can potentially be used for both navigation and non-navigation tasks resulting in a productive and lightweight UA system that is able to avoid or reduce regulatory burdens for GPS denied UA operations