Cooperative distributed LQR control for longitudinal flight of a formation of non-identical low-speed experimental UAV's

In this paper, an established distributed LQR control methodology applied to identical linear systems is extended to control arbitrary formations of non-identical UAV's. The nonlinear model of a low-speed experimental UAV known as X-RAE1 is utilized for simulation purposes. The formation is composed of four dynamically decoupled X-RAE1 which differ in their masses and their products of inertia about the xz plane. In order to design linear controllers the nonlinear models are linearized for horizontal flight conditions at constant velocity. State-feedback, input and similarity transformations are applied to solve model-matching type problems and compensate for the mismatch in the linearized models due to mass and symmetry discrepancies among the X-RAE1 models. It is shown that the method is based on the controllability indices of the linearized models. Distributed LQR control employed in networks of identical linear systems is appropriately adjusted and applied to the formation of the nonidentical UAV's. The applicability of the approach is illustrated via numerous simulation results

Measuring cycle riding comfort in Southampton using an instrumented bicycle

The increased environmental awareness and the rising fuel costs make bicycles a more and more attractive mode of travel for short journeys. Considering the future prospect of this mode of transportation and the great advantages that it offers in terms of space consumption, health and environmental sustainability, several city authorities worldwide are presently undertaking schemes aiming at improving cycling infrastructure. The aim of the present study is to monitor the impact of such schemes on the riding comfort of cyclists, as expressed by the, usually lower, quantity and magnitude of vibrations occurring as a result of cycling over pavement defects. Millbrook Road East in the western edge of the city center of Southampton is used as a case study, where vibration measurements are taken by means of an instrumented bicycle during periods before and after a redevelopment scheme involving the resurfacing of the road pavement. The results show a clear overall improvement in cycling comfort post-redevelopment, with statistically significant reductions in both the number of high severity vibrations and of their magnitude in "typical" cycling trips taken on the road. However, instances of finishing "snags" in some parts of the surface appear to introduce new minor defects (e.g. around manholes) that are not visible to the naked eye, and these still have some negative effect on the riding experience. Moreover, the study highlights the detrimental impact that widespread pavement defects can have on riding comfort, which affect cyclists of all ages, abilities and styles

An Innovative Multi-Sensor Fusion Algorithm to Enhance Positioning Accuracy of an Instrumented Bicycle

Cycling is an increasingly popular mode of travel in cities, but its poor safety record currently acts as a hurdle to its wider adoption as a real alternative to the private car. A particular source of hazard appears to originate from the interaction of cyclists with motorized traffic at low speeds in urban areas. But while technological advances in recent years have resulted in numerous attempts at systems for preventing cyclist-vehicle collisions, these have generally encountered the challenge of accurate cyclist localization. This paper addresses this challenge by introducing an innovative bicycle localization algorithm, which is derived from the geometrical relationships and kinematics of bicycles. The algorithm relies on the measurement of a set of kinematic variables (such as yaw, roll, and steering angles) through low-cost on-board sensors. It then employs a set of Kalman filters to predict-correct the direction and position of the bicycle and fuse the measurements in order to improve positioning accuracy. The capabilities of the algorithm are then demonstrated through a real-world field experiment using an instrumented bicycle, called ``iBike'', in an urban environment. The results show that the proposed fusion achieves considerably lower positioning errors than that would be achieved based on dead-reckoning alone, which makes the algorithm a credible basis for the development of future collision warning and avoidance systems

Finite settling time stabilization for linear multivariable time-invariant discrete-time systems: An algebraic approach

The problem of Total Finite Settling Time Stabilization of linear time-invariant discrete-time systems is investigated in this thesis. This problem falls within the same area of the well-known deadbeat (time-optimal) control and in particular, constitutes a generalization of this problem. That is, instead of seeking time-optimum performance, it is required that all internal and external variables (signals) of the closed-loop system settle to a new steady state after a finite time from the application of a step change to any of its inputs and for every initial condition. The state/output deadbeat control is a special case of the Total FSTS problem. Using a mathematical and system theory framework based on sequences and the polynomial equation (algebraic) approach, we are able to tackle the FSTS problem in a unifying manner. The one-parameter (unity) feedback configuration is mainly used for the solution of the FSTS problem and FSTS related control strategies. The whole problem is reduced to the solution of a polynomial matrix Diophantine equation which guarantees not only internal stability but also internal FSTS and is further reduced to the solution of a linear algebra problem over R. This approach enables the parametrizat ion of the family of all FSTS controllers, as well as those which are causal, in a Youla-Bongiorno-Kucera type parametrization. The minimal McMillan degree FSTS problem is completely solved for vector plants and a parametrization of the FSTS controllers according to their McMillan degree is obtained. In the MIMO case bounds of the minimum McMillan degree controllers are derived and families of FSTS controllers with given lower/upper McMillan degree bounds are provided in parametric form. Having parametrized the family of all FSTS controllers, the state deadbeat regulation is treated as a special case of FSTS and complete parametrization of all the deadbeat regulators is presented. In addition, further performance criteria, or design constraints are imposed such as, FSTS tracking and/or disturbance rejection, partial assignment of controller dynamics, l1-, l∞-optimization and robustness to plant parameter variations. Finally, the Simultaneous-FSTS problem is formulated, and necessary as well as sufficient conditions for its solution are derived. Also, a two-parameter control scheme is introduced to alleviate some of the drawbacks of the one-parameter control. A parametrization of the family of FSTS controllers as well as the FSTS controllers for tracking and/or disturbance rejection is given as an illustration of the particular advantages of the two-parameter FSTS controllers

Cyclist 360° Alert: Validation of an Instrumented Bicycle Trajectory Reconstruction Mechanism Using Satellite and Inertial Navigation Systems

Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability. However, the number of recent accidents between cyclists and heavy goods vehicles has increased substantially. Our study shows that one of the main causes of accidents is drivers not being able to observe cyclists. Thus, this research reported here involves the development of an innovative low-cost technological solution called Cyclist 360° Alert and as an integral part of this system, this paper focuses on the bicycle localization aspect and presents an approach based on low-cost micro-electromechanical systems (MEMS) sensor con figurations on an instrumented prototype bicycle system, called “iBike”. The iBike has the capability of sensing its motion, which can be then analysed to compute the trajectory path. The paper describes the overall system of the instrumented bicycle which incorporates an Inertial Navigation System (INS) and a Global Navigation Satellite System (GNSS) receiver. The paper then evaluates and compare the accuracy of the three positioning systems using experimental field data. Finally, the paper also draws conclusions on the applicability of specific sensor configurations, both in terms of sensors’ accuracy and reliability with respect to the measurements of motion, and the ability of tracking trajectories based on the data gathered from the sensor

Automating the processing of cDNA microarray images

This work is concerned with the development of an automatic image processing tool for DNA microarray images. This paper proposes, implements and tests a new tool for cDNA image analysis. The DNAs are imaged as thousands of circularly shaped objects (spots) on the microarray image and the purpose of this tool is to correctly address their location, segment the pixels belonging to spots and extract the quality features of each spot. Techniques used for addressing, segmentation and feature extraction of spots are described in detail. The results obtained with the proposed tool are systematically compared with conventional cDNA microarray analysis software tools

LQR distributed cooperative control of a formation of low-speed experimental UAVs

The paper presents a cooperative scheme for controlling arbitrary formations of low speed experimental UAVs based on a distributed LQR design methodology. Each UAV acts as an independent agent in the formation and its dynamics are described by a 6-DOF (degrees of freedom) nonlinear model. This is linearized for control design purposes around an operating point corresponding to straight flight conditions and simulated only for longitudinal motion. It is shown that the proposed controller stabilizes the overall formation and can control effectively the nonlinear multi-agent system. Also, it is shown via numerous simulations that the system provides reference tracking and that is robust to environmental disturbances such as nonuniform wind gusts acting on a formation of four UAVs and to the loss of communication between two neighbouring UAVs

Finite settling time stabilisation: the robust SISO case

This article deals with the problem of robustness to multiplicative plant perturbations for the case of finite settling time stabilisation (FSTS) of single input single output (SISO), linear, discrete-time systems. FSTS is a generalisation of the deadbeat control and as in the case of deadbeat control the main feature of FSTS is the placement of all closed-loop poles at the origin of the z-plane. This makes FSTS sensitive to plant perturbations hence, the need of robust design. An efficient robustness index is introduced and the problem is reduced to a finite linear programme where all the benefits of the simplex method, such as effectiveness, efficiency and ability to provide complete solution to the optimisation problem, can be exploited

The development of the mathematical model of an RPV and an investigation on the use of an EKF for the identification of its aerodynamic derivatives

A six-degrees of freedom mathematical model of an experimental Remotely Piloted Vehicle (RPV) and the linearised longitudinal and lateral models at 30m/sec are developed. The longitudinal and lateral dynamics are analysed and the equivalent discrete systems are used to provide baseline data for the identification of the aerodynamic derivatives of the RPV. An advanced aircraft parameter estimation method - the Extended Kalman Filter - is implemented for the estimation of the aerodynamic characteristics of the RPV. Conclusions are drawn about the identifiability of the stability and control derivatives from pitch, roll and yaw rate measurements