Closed-loop nonlinear optimal control design for flapping-wing flying robot (1.6 m wingspan) in indoor confined space: Prototyping, modeling, simulation, and experiment

This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).The flapping-wing technology has emerged recently in the application of unmanned aerial robotics for autonomous flight, control, inspection, monitoring, and manipulation. Despite the advances in applications and outdoor manual flights (open-loop control), closed-loop control is yet to be investigated. This work presents a nonlinear optimal closed-loop control design via the state-dependent Riccati equation (SDRE) for a flapping-wing flying robot (FWFR). Considering that the dynamic modeling of the flapping-wing robot is complex, a proper model for the implementation of nonlinear control methods is demanded. This work proposes an alternative approach to deliver an equivalent dynamic for the translation of the system and a simplified model for orientation, to find equivalent dynamics for the whole system. The objective is to see the effect of flapping (periodic oscillation) on behavior through a simple model in simulation. Then the SDRE controller is applied to the derived model and implemented in simulations and experiments. The robot bird is a 1.6 m wingspan flapping-wing system (six-degree-of-freedom robot) with four actuators, three in the tail, and one as the flapping input. The underactuated system has been controlled successfully in position and orientation. The control loop is closed by the motion capture system in the indoor test bed where the experiments of flight have been successfully done

Nonlinear Systems

Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in physics and mathematics, as well as in many other fields, as highly correlated nonlinear phenomena, evolving over a large range of time scales and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods. The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects. Potential topics include, but are not limited to: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems

Kernel-based fault diagnosis of inertial sensors using analytical redundancy

Kernel methods are able to exploit high-dimensional spaces for representational advantage, while only operating implicitly in such spaces, thus incurring none of the computational cost of doing so. They appear to have the potential to advance the state of the art in control and signal processing applications and are increasingly seeing adoption across these domains. Applications of kernel methods to fault detection and isolation (FDI) have been reported, but few in aerospace research, though they offer a promising way to perform or enhance fault detection. It is mostly in process monitoring, in the chemical processing industry for example, that these techniques have found broader application. This research work explores the use of kernel-based solutions in model-based fault diagnosis for aerospace systems. Specifically, it investigates the application of these techniques to the detection and isolation of IMU/INS sensor faults – a canonical open problem in the aerospace field. Kernel PCA, a kernelised non-linear extension of the well-known principal component analysis (PCA) algorithm, is implemented to tackle IMU fault monitoring. An isolation scheme is extrapolated based on the strong duality known to exist between probably the most widely practiced method of FDI in the aerospace domain – the parity space technique – and linear principal component analysis. The algorithm, termed partial kernel PCA, benefits from the isolation properties of the parity space method as well as the non-linear approximation ability of kernel PCA. Further, a number of unscented non-linear filters for FDI are implemented, equipped with data-driven transition models based on Gaussian processes - a non-parametric Bayesian kernel method. A distributed estimation architecture is proposed, which besides fault diagnosis can contemporaneously perform sensor fusion. It also allows for decoupling faulty sensors from the navigation solution

Natural and artificial orbits around the Martian moon Phobos

One of the paramount stepping stones towards the long-term goal of undertaking human missions to Mars is the exploration of the Martian moons. In particular, Phobos is becoming an appealing destination for future scientific missions of NASA and ESA. Phobos is a tiny celestial body that orbits around Mars at low altitude. The unique combination of these two characteristics yields the sphere of influence of the moon to be very close to its surface. Therefore, orbital dynamics around Phobos are particularly complex, because many strong perturbations are involved. The classical models of the Keplerian two-body problem, and the circular three-body problem are not accurate enough to describe the motion of a spacecraft in the vicinity of Phobos. In this thesis, the description of the relative orbital dynamics in proximity of this moon is extended to a more accurate nonlinear model. This is undertaken by the inclusion of the perturbations due to the orbital eccentricity and the inhomogeneous gravity field of Phobos. Subsequently, several classes of non-Keplerian orbits are identified, using the analytical and numerical methodologies of dynamical systems theory. These techniques exploit the improved description of the natural dynamics, enabled by the extended model, to provide low-cost guidance trajectories, that minimize the fuel consumption and extend the mission range. In addition, the potential of exploiting artificial orbits with lowthrust is investigated. The performance and requirements of these orbits are assessed, and a number of potential mission applications near Phobos are proposed. These low-cost operations include close-range observation, communication, passive radiation shielding, and orbital pitstops for human space flight. These results could be exploited in upcoming missions targeting the exploration of this Martian moon. Furthermore, the new model can provide evidence to support the accretion theory of Phobos' origin, and to explain the formation of the craters and grooves on Phobos

The role of tree height and wood density for the water use, productivity and hydraulic architecture of tropical trees

Tropical forests are the world’s most productive terrestrial ecosystems and of central importance for global carbon and water cycles. Global climate projections predict increases in average temperature and an elevated frequency of extreme drought events throughout large parts of the tropics. In response to these changes, increases in mortality rates particularly among large trees have already been reported for many tropical forest ecosystems. Hence, there is a need for better predictions of the performance of tropical forest trees under more frequent drought conditions, which the present work seeks to address a) by more accurately quantifying how much water plants use and b) by advancing the knowledge about plant traits and mechanisms that control plant water use, growth performance and drought responses. To achieve this, this study is separated in two parts, the first of which aims at methodological improvements of water use and transpiration estimates, while the second part focuses on disentangling the relationship between tree height, wood density and wood anatomical properties, and quantifying their common effect on the productivity and water relations. The backbone of this thesis is formed by data from a field study on five research sites situated on a rainfall gradient along the Pacific coastline of Costa Rica, which are complemented by additional results from a laboratory-based study of sap flux sensor performance and a large observational dataset from tropical forests in Indonesia. In Part I, I first present accessory results from a laboratory-based calibration experiment based on 66 stems from five temperate diffuse-porous tree species. Three commonly applied sensor systems, thermal dissipation probes (TDP), heat field deformation (HFD) sensors, and heat ratio method (HRM) sensors, were validated against gravimetrically determined flow rates to compare them in terms of bias, precision and accuracy. Our results indicate a systematic underestimation of true sap flux density by on average 23-45% with the TDP method, and a relatively low precision (but lower bias) with HFD sensors. The best performance was observed for HRM sensors if restricted to low flow ranges. Based on the methods comparison, we conclude that the TDP and HFD methods require species-specific empirical calibration for optimal performance, and that for all methods there is a within-species variability in calibration relationships that puts a limit on accuracy. In the light of these findings, I then discuss the outcome of a field study of sap flux measurements using the HFD method. In this work, we analyzed a dataset of sap flow measurements from 38 trees belonging to eight tropical dry forest tree species from Costa Rica. Based on a Bayesian hierarchical modelling approach, we developed a model for radial sap flux profiles that allowed to propagate model uncertainty when predicting the shape of HFD-based radial profiles onto new trees and new tree species, and describe how to integrate these model predictions with single-point sensor readings from other sensor systems in order to improve their accuracy. We found that tree height had a credible effect on both the shape of radial profiles and whole-tree water use, with larger trees having the bulk of flow closer to the bark and reaching higher transpiration rates. Compared to water use estimates based on radial profiles, estimates that assumed constant flow over the entire sapwood overestimated water use by 26% on average. In Part II, I first show results from a dataset comprising trait averages from 99 tropical forest tree species from Sumatra and Sulawesi (Indonesia). In this study, we used structural equation models (SEM) to analyze the relationships between tree size, wood density, wood anatomical traits related to hydraulic efficiency, empirically determined sap flux density, biomass productivity and tree water use, and compared the results to simple bivariate associations. We found a strong correlation between water use and growth, which was completely explained by their common dependence on tree size and sap flux density. While wood hydraulic traits were closely associated with growth and water use, our model suggested that this relationship was mainly driven by a confounding size effect. After accounting for tree size, only a relatively small effect of wood properties remained that was mediated by sap flux density. I then present a second SEM-based study that builds upon data from 201 tropical rainforest trees belonging to 40 species distributed along the rainfall gradient in Costa Rica. In this study, we found a strong dependence of biomass increment from canopy position and tree diameter, while the effects of wood density and wood hydraulic traits diminished after controlling for size effects. Notably, differences in growth along the rainfall gradient were completely explained by the effect of annual precipitation on canopy height. We further found trees belonging to species that are more affiliated to drier habitats to have smaller sapwood nonstructural carbohydrate concentrations and to be more common in the upper canopy. Supplementary, unpublished results from an analysis of vulnerability curves measured from Costa Rican tropical rainforest trees indicate that the strong size effect in growth, water use and wood hydraulic trees surprisingly was mirrored by a size dependence in embolism resistance, with the highest embolism resistance in the largest and most fast-growing species. In addition, we found embolism resistance to be strongly associated with stem sapwood properties, with a significantly higher embolism resistance for species with harder wood and lower vessel diameters. In summary, the present work provides a set of methodological refinements to sap flow measurement methodology that has the potential to significantly improve the accuracy of tree level transpiration estimates. In addition, it adds to the growing body of evidence indicating that tree size and/or canopy position are important covariates that have to be controlled for when studying relationships between plant traits. In particular, we show that observed positive correlations of biomass increment and water use with wood properties can largely be attributed to a confounding size effect, which suggests that the functional importance of wood anatomical traits may often be overstated

Machine Learning

Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience

An Approach for Multi-Robot Opportunistic Coexistence in Shared Space

This thesis considers a situation in which multiple robots operate in the same environment towards the achievement of different tasks. In this situation, please consider that not only the tasks, but also the robots themselves are likely be heterogeneous, i.e., different from each other in their morphology, dynamics, sensors, capabilities, etc. As an example, think about a "smart hotel": small wheeled robots are likely to be devoted to cleaning floors, whereas a humanoid robot may be devoted to social interaction, e.g., welcoming guests and providing relevant information to them upon request. Under these conditions, robots are required not only to co-exist, but also to coordinate their activity if we want them to exhibit a coherent and effective behavior: this may range from mutual avoidance to avoid collisions, to a more explicit coordinated behavior, e.g., task assignment or cooperative localization. The issues above have been deeply investigated in the Literature. Among the topics that may play a crucial role to design a successful system, this thesis focuses on the following ones: (i) An integrated approach for path following and obstacle avoidance is applied to unicycle type robots, by extending an existing algorithm [1] initially developed for the single robot case to the multi-robot domain. The approach is based on the definition of the path to be followed as a curve f (x;y) in space, while obstacles are modeled as Gaussian functions that modify the original function, generating a resulting safe path. The attractiveness of this methodology which makes it look very simple, is that it neither requires the computation of a projection of the robot position on the path, nor does it need to consider a moving virtual target to be tracked. The performance of the proposed approach is analyzed by means of a series of experiments performed in dynamic environments with unicycle-type robots by integrating and determining the position of robot using odometry and in Motion capturing environment. (ii) We investigate the problem of multi-robot cooperative localization in dynamic environments. Specifically, we propose an approach where wheeled robots are localized using the monocular camera embedded in the head of a Pepper humanoid robot, to the end of minimizing deviations from their paths and avoiding each other during navigation tasks. Indeed, position estimation requires obtaining a linear relationship between points in the image and points in the world frame: to this end, an Inverse Perspective mapping (IPM) approach has been adopted to transform the acquired image into a bird eye view of the environment. The scenario is made more complex by the fact that Pepper\u2019s head is moving dynamically while tracking the wheeled robots, which requires to consider a different IPM transformation matrix whenever the attitude (Pitch and Yaw) of the camera changes. Finally, the IPM position estimate returned by Pepper is merged with the estimate returned by the odometry of the wheeled robots through an Extened Kalman Filter. Experiments are shown with multiple robots moving along different paths in a shared space, by avoiding each other without onboard sensors, i.e., by relying only on mutual positioning information. Software for implementing the theoretical models described above have been developed in ROS, and validated by performing real experiments with two types of robots, namely: (i) a unicycle wheeled Roomba robot(commercially available all over the world), (ii) Pepper Humanoid robot (commercially available in Japan and B2B model in Europe)

14th Conference on Dynamical Systems Theory and Applications DSTA 2017 ABSTRACTS

From Preface: This is the fourteen time when the conference “Dynamical Systems – Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and the Ministry of Science and Higher Education. It is a great pleasure that our invitation has been accepted by so many people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcome nearly 250 persons from 38 countries all over the world. They decided to share the results of their research and many years experiences in the discipline of dynamical systems by submitting many very interesting papers. This booklet contains a collection of 375 abstracts, which have gained the acceptance of referees and have been qualified for publication in the conference proceedings [...]