1000 resultados para ADAPTIVE STABILIZATION


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We propose a discontinuous-Galerkin-based immersed boundary method for elasticity problems. The resulting numerical scheme does not require boundary fitting meshes and avoids boundary locking by switching the elements intersected by the boundary to a discontinuous Galerkin approximation. Special emphasis is placed on the construction of a method that retains an optimal convergence rate in the presence of non-homogeneous essential and natural boundary conditions. The role of each one of the approximations introduced is illustrated by analyzing an analog problem in one spatial dimension. Finally, extensive two- and three-dimensional numerical experiments on linear and nonlinear elasticity problems verify that the proposed method leads to optimal convergence rates under combinations of essential and natural boundary conditions. (C) 2009 Elsevier B.V. All rights reserved.

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The idea of spacecraft formations, flying in tight configurations with maximum baselines of a few hundred meters in low-Earth orbits, has generated widespread interest over the last several years. Nevertheless, controlling the movement of spacecraft in formation poses difficulties, such as in-orbit high-computing demand and collision avoidance capabilities, which escalate as the number of units in the formation is increased and complicated nonlinear effects are imposed to the dynamics, together with uncertainty which may arise from the lack of knowledge of system parameters. These requirements have led to the need of reliable linear and nonlinear controllers in terms of relative and absolute dynamics. The objective of this thesis is, therefore, to introduce new control methods to allow spacecraft in formation, with circular/elliptical reference orbits, to efficiently execute safe autonomous manoeuvres. These controllers distinguish from the bulk of literature in that they merge guidance laws never applied before to spacecraft formation flying and collision avoidance capacities into a single control strategy. For this purpose, three control schemes are presented: linear optimal regulation, linear optimal estimation and adaptive nonlinear control. In general terms, the proposed control approaches command the dynamical performance of one or several followers with respect to a leader to asymptotically track a time-varying nominal trajectory (TVNT), while the threat of collision between the followers is reduced by repelling accelerations obtained from the collision avoidance scheme during the periods of closest proximity. Linear optimal regulation is achieved through a Riccati-based tracking controller. Within this control strategy, the controller provides guidance and tracking toward a desired TVNT, optimizing fuel consumption by Riccati procedure using a non-infinite cost function defined in terms of the desired TVNT, while repelling accelerations generated from the CAS will ensure evasive actions between the elements of the formation. The relative dynamics model, suitable for circular and eccentric low-Earth reference orbits, is based on the Tschauner and Hempel equations, and includes a control input and a nonlinear term corresponding to the CAS repelling accelerations. Linear optimal estimation is built on the forward-in-time separation principle. This controller encompasses two stages: regulation and estimation. The first stage requires the design of a full state feedback controller using the state vector reconstructed by means of the estimator. The second stage requires the design of an additional dynamical system, the estimator, to obtain the states which cannot be measured in order to approximately reconstruct the full state vector. Then, the separation principle states that an observer built for a known input can also be used to estimate the state of the system and to generate the control input. This allows the design of the observer and the feedback independently, by exploiting the advantages of linear quadratic regulator theory, in order to estimate the states of a dynamical system with model and sensor uncertainty. The relative dynamics is described with the linear system used in the previous controller, with a control input and nonlinearities entering via the repelling accelerations from the CAS during collision avoidance events. Moreover, sensor uncertainty is added to the control process by considering carrier-phase differential GPS (CDGPS) velocity measurement error. An adaptive control law capable of delivering superior closed-loop performance when compared to the certainty-equivalence (CE) adaptive controllers is finally presented. A novel noncertainty-equivalence controller based on the Immersion and Invariance paradigm for close-manoeuvring spacecraft formation flying in both circular and elliptical low-Earth reference orbits is introduced. The proposed control scheme achieves stabilization by immersing the plant dynamics into a target dynamical system (or manifold) that captures the desired dynamical behaviour. They key feature of this methodology is the addition of a new term to the classical certainty-equivalence control approach that, in conjunction with the parameter update law, is designed to achieve adaptive stabilization. This parameter has the ultimate task of shaping the manifold into which the adaptive system is immersed. The performance of the controller is proven stable via a Lyapunov-based analysis and Barbalat’s lemma. In order to evaluate the design of the controllers, test cases based on the physical and orbital features of the Prototype Research Instruments and Space Mission Technology Advancement (PRISMA) are implemented, extending the number of elements in the formation into scenarios with reconfigurations and on-orbit position switching in elliptical low-Earth reference orbits. An extensive analysis and comparison of the performance of the controllers in terms of total Δv and fuel consumption, with and without the effects of the CAS, is presented. These results show that the three proposed controllers allow the followers to asymptotically track the desired nominal trajectory and, additionally, those simulations including CAS show an effective decrease of collision risk during the performance of the manoeuvre.

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Locomotion is of fundamental importance in understanding adaptive behavior. In this paper we present two case studies of robot locomotion that demonstrate how higher level of behavioral diversity can be achieved while observing the principle of cheap design. More precisely, it is shown that, by exploiting the dynamics of the system-environment interaction, very simple controllers can be designed which is essential to achieve rapid locomotion. Special consideration must be given to the choice of body materials. We conclude with some speculation about the importance of locomotion for understanding cognition. © Springer-Verlag Berlin Heidelberg 2004.

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Various piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films depend on charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to deteriorate owing to strong vacuum UV, � -, X-ray, energetic particles and atomic oxygen exposure. We have investigated the degradation of PVDF and its copolymers under various stress environments detrimental to reliable operation in space. Initial radiation aging studies have shown complex material changes with lowered Curie temperatures, complex material changes with lowered melting points, morphological transformations and significant crosslinking, but little influence on piezoelectric d33 constants. Complex aging processes have also been observed in accelerated temperature environments inducing annealing phenomena and cyclic stresses. The results suggest that poling and chain orientation are negatively affected by radiation and temperature exposure. A framework for dealing with these complex material qualification issues and overall system survivability predictions in low earth orbit conditions has been established. It allows for improved material selection, feedback for manufacturing and processing, material optimization/stabilization strategies and provides guidance on any alternative materials.

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Ligand-induced stabilization of the G-quadruplex DNA structure derived from the single-stranded 3'-overhang of the telomeric DNA is an attractive strategy for the inhibition of the telomerase activity. The agents that can induce/stabilize a DNA sequence into a G-quadruplex structure are therefore potential anticancer drugs. Herein we present the first report of the interactions of two novel bisbenzimidazoles (TBBz1 and TBBz2) based on Troger's base skeleton with the G-quadruplex DNA (G4DNA). These Troger's base molecules stabilize the G4DNA derived from a human telomeric sequence. Evidence of their strong interaction with the G4DNA has been obtained from CD spectroscopy, thermal denaturation, and UV-vis titration studies. These ligands also possess significantly higher affinity toward the G4DNA over the duplex DNA. The above results obtained are in excellent agreement with the biological activity, measured in vitro using a modified TRAP assay. Furthermore, the ligands are selectively more cytotoxic toward the cancerous cells than the corresponding noncancerous cells. Computational studies suggested that the adaptive scaffold might allow these ligands to occupy not only the G-quartet planes but also the grooves of the G4DNA.

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This paper investigates the local asymptotic stabilization of a very general class of instable autonomous nonlinear difference equations which are subject to perturbed dynamics which can have a different order than that of the nominal difference equation. In the general case, the controller consists of two combined parts, namely, the feedback nominal controller which stabilizes the nominal (i.e., perturbation-free) difference equation plus an incremental controller which completes the stabilization in the presence of perturbed or unmodeled dynamics in the uncontrolled difference equation. A stabilization variant consists of using a single controller to stabilize both the nominal difference equation and also the perturbed one under a small-type characterization of the perturbed dynamics. The study is based on Banach fixed point principle, and it is also valid with slight modification for the stabilization of unstable oscillatory solutions.

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There is much to gain from providing walking machines with passive dynamics, e.g. by including compliant elements in the structure. These elements can offer interesting properties such as self-stabilization, energy efficiency and simplified control. However, there is still no general design strategy for such robots and their controllers. In particular, the calibration of control parameters is often complicated because of the highly nonlinear behavior of the interactions between passive components and the environment. In this article, we propose an approach in which the calibration of a key parameter of a walking controller, namely its intrinsic frequency, is done automatically. The approach uses adaptive frequency oscillators to automatically tune the intrinsic frequency of the oscillators to the resonant frequency of a compliant quadruped robot The tuning goes beyond simple synchronization and the learned frequency stays in the controller when the robot is put to halt. The controller is model free, robust and simple. Results are presented illustrating how the controller can robustly tune itself to the robot, as well as readapt when the mass of the robot is changed. We also provide an analysis of the convergence of the frequency adaptation for a linearized plant, and show how that analysis is useful for determining which type of sensory feedback must be used for stable convergence. This approach is expected to explain some aspects of developmental processes in biological and artificial adaptive systems that "develop" through the embodied system-environment interactions. © 2006 IEEE.

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This paper introduces a new class of predictive ART architectures, called Adaptive Resonance Associative Map (ARAM) which performs rapid, yet stable heteroassociative learning in real time environment. ARAM can be visualized as two ART modules sharing a single recognition code layer. The unit for recruiting a recognition code is a pattern pair. Code stabilization is ensured by restricting coding to states where resonances are reached in both modules. Simulation results have shown that ARAM is capable of self-stabilizing association of arbitrary pattern pairs of arbitrary complexity appearing in arbitrary sequence by fast learning in real time environment. Due to the symmetrical network structure, associative recall can be performed in both directions.

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This paper presents a nonlinear robust adaptive excitation controller design for a simple power system model where a synchronous generator is connected to an infinite bus. The proposed controller is designed to obtain the adaption laws for estimating critical parameters of synchronous generators which are considered as unknown while providing the robustness against the bounded external disturbances. The convergence of different physical quantities of a single machine infinite bus (SMIB) system, with the proposed control scheme, is ensured through the negative definiteness of the derivative of Lyapunov functions. The effects of external disturbances are considered during formulation of Lyapunov function and thus, the proposed excitation controller can ensure the stability of the SMIB system under the variation of critical parameters as well as external disturbances including noises. Finally, the performance of the proposed scheme is investigated with the inclusion of external disturbances in the SMIB system and its superiority is demonstrated through the comparison with an existing robust adaptive excitation controller. Simulation results show that the proposed scheme provides faster responses of physical quantities than the existing controller.

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This work investigated the effects of frequency and precision of feedback on the learning of a dual-motor task. One hundred and twenty adults were randomly assigned to six groups of different knowledge of results (KR), frequency (100%, 66% or 33%) and precision (specific or general) levels. In the stabilization phase, participants performed the dual task (combination of linear positioning and manual force control) with the provision of KR. Ten non-KR adaptation trials were performed for the same task, but with the introduction of an electromagnetic opposite traction force. The analysis showed a significant main effect for frequency of KR. The participants who received KR in 66% of the stabilization trials showed superior adaptation performance than those who received 100% or 33%. This finding reinforces that there is an optimal level of information, neither too high nor too low, for motor learning to be effective.