An approach to multi-fidelity optimization of aeroengine compression systems

The aerodynamic design of turbomachinery presents the design optimisation community with a number of exquisite challenges. Chief among these are the size of the design space and the extent of discontinuity therein. This discontinuity can serve to limit the full exploitation of high-fidelity computational fluid dynamics (CFD): such codes require detailed geometric information often available only sometime after the basic configuration of the machine has been set by other means. The premise of this paper is that it should be possible to produce higher performing designs in less time by exploiting multi-fidelity techniques to effectively harness CFD earlier in the design process, specifically by facilitating its participation in configuration selection. The adopted strategy of local multi-fidelity correction, generated on demand, combined with a global search algorithm via an adaptive trust region is first tested on a modest, smooth external aerodynamic problem. Speed-up of an order of magnitude is demonstrated, comparable to established techniques applied to smooth problems. A number of enhancements aimed principally at effectively evaluating a wide range of configurations quickly is then applied to the basic strategy, and the emerging technique is tested on a generic aeroengine core compression system. A similar order of magnitude speed-up is achieved on this relatively large and highly discontinuous problem. A five-fold increase in the number of configurations assessed with CFD is observed. As the technique places constraints neither on the underlying physical modelling of the constituent analysis codes nor on first-order agreement between those codes, it has potential applicability to a range of multidisciplinary design challenges. © 2012 by Jerome Jarrett and Tiziano Ghisu.

A self-adaptive genetic algorithm applied to multi-objective optimization of an airfoil

Genetic algorithms (GAs) have been used to tackle non-linear multi-objective optimization (MOO) problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the numbers of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimizing GA (MOGA) that uses self-adaptive mutation and crossover, and which is applied to optimization of an airfoil, for minimization of drag and maximization of lift coefficients. The MOGA is integrated with a Free-Form Deformation tool to manage the section geometry, and XFoil which evaluates each airfoil in terms of its aerodynamic efficiency. The performance is compared with those of the heuristic MOO algorithms, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this GA achieves better convergence.

Adaptive combustion instability control with saturation

The control of a class of combustion systems, suceptible to damage from self-excited combustion oscillations, is considered. An adaptive stable controller, called Self-Tuning Regulator (STR), has recently been developed, which meets the apparently contradictory challenge of relying as little as possible on a particular combustion model while providing some guarantee that the controller will cause no harm. The controller injects some fuel unsteadily into the burning region, thereby altering the heat release, in response to an input signal detecting the oscillation. This paper focuses on an extension of the STR design, when, due to stringent emission requirements and to the danger of flame extension, the amount of fuel used for control is limited in amplitude. A Lyapunov stability analysis is used to prove the stability of the modified STR when the saturation constraint is imposed. The practical implementation of the modified STR remains straightforward, and simulation results, based on the nonlinear premixed flame model developed by Dowling, show that in the presence of a saturation constraint, the self-excited oscillations are damped more rapidly with the modified STR than with the original STR. © 2001 by S. Evesque. Published by the American Institute of Aeronautics and Astronautics, Inc.

New robotics: design principles for intelligent systems.

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

Morphological computation for adaptive behavior and cognition

Traditionally, in robotics, artificial intelligence and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest in the notion of embodiment not only in robotics and artificial intelligence, but also in the neurosciences, psychology and philosophy. In this paper, we introduce the notion of morphological computation, and demonstrate how it can be exploited on the one hand for designing intelligent, adaptive robotic systems, and on the other hand for understanding natural systems. While embodiment has often been used in its trivial meaning, i.e. "intelligence requires a body", the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. Morphological computation is about connecting body, brain and environment. A number of case studies are presented to illustrate the concept. We conclude with some speculations about potential lessons for neuroscience and robotics. © 2006 Elsevier B.V. All rights reserved.

An adaptive controller for a class of nonlinear system using direction basis function

For a class of nonlinear dynamical systems, the adaptive controllers are investigated using direction basis function (DBF) in this paper. Based on the criterion of Lyapunov' stability, DBF is designed which guarantees that the output of the controlled system asymptotically tracks the reference signals. Finally, the simulation shows the good tracking effectiveness of the adaptive controller.

An adaptive frequency synthesizer architecture reducing reference sidebands

An adaptive phase-locked loop (PLL) frequency synthesizer architecture for reducing reference sidebands at the output of the frequency synthesizer is described. The architecture combines two tuning loops: one is the main loop for locking the PLL frequency synthesizer and operating all the time, the other one is auxiliary loop for reducing reference sidebands and operating only when the main loop is closely locked. A 1.8V 1GHz fully integrated CMOS dual-loop frequency synthesizer is designed in a 0.18um CMOS process. The suppression of the reference sidebands of the proposed frequency synthesizer is 13.8dB more than that of the general frequency synthesizer.

Modal correction for fiber-coupling efficiency in free-space optical communication systems through atmospheric turbulence

High-speed free-space optical communication systems have recently used fiber-optical components. The coupling efficiency with which the received laser beam can be coupled into a single-mode fiber is noticeably limited by atmospheric turbulence due to the degradation of its spatial coherence. Fortunately, adaptive optics (AO) can alleviate this limitation by partially correcting the turbulence-distorted wavefront. The coupling efficiency improvement provided by Zernike modal AO correction is numerically evaluated. It is found that the first 3-20 corrected polynomials can considerably improve the fiber-coupling efficiency. The improvement brought by AO is compared with that brought by a coherent fiber array. Finally, a hybrid technique that integrates AO and a coherent fiber array is proposed. Results show that the hybrid technique outperforms each of the two above-mentioned techniques. (C) 2009 Elsevier GmbH. All rights reserved.

adaptive location update mechanism for network-constrained moving objects in changeful traffic conditions

Natl Chiao Tung Univ, Dept Comp Sci

Minimizing Residual Vibrations in Flexible Systems

Residual vibrations degrade the performance of many systems. Due to the lightweight and flexible nature of space structures, controlling residual vibrations is especially difficult. Also, systems such as the Space Shuttle remote Manipulator System have frequencies that vary significantly based upon configuration and loading. Recently, a technique of minimizing vibrations in flexible structures by command input shaping was developed. This document presents research completed in developing a simple, closed- form method of calculating input shaping sequences for two-mode systems and a system to adapt the command input shaping technique to known changes in system frequency about the workspace. The new techniques were tested on a three-link, flexible manipulator.

Lifelong Evolution for Adaptive Robots

Walker,J. and Wilson,M.S., 'Lifelong Evolution for Adaptive Robots', Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2002, October, pp 984--989

Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

Q. Meng and M. H Lee, Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks, Connection Science, 19(1), pp 25-52, 2007.

Biologically inspired automatic construction of cross-modal mapping in robotic eye/hand systems

Q. Meng and M.H. Lee, 'Biologically inspired automatic construction of cross-modal mapping in robotic eye/hand systems', IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006,) ,4742-49, Beijing, 2006.

Adaptive capacity and learning to learn as leverage for social-ecological resilience

Ioan Fazey, John A. Fazey, Joern Fischer, Kate Sherren, John Warren, Reed F. Noss, Stephen R. Dovers (2007) Adaptive capacity and learning to learn as leverage for social?ecological resilience. Frontiers in Ecology and the Environment 5(7),375-380. RAE2008

BitBox!: A case study interface for teaching real-time adaptive music composition for video games

Real-time adaptive music is now well-established as a popular medium, largely through its use in video game soundtracks. Commercial packages, such as fmod, make freely available the underlying technical methods for use in educational contexts, making adaptive music technologies accessible to students. Writing adaptive music, however, presents a significant learning challenge, not least because it requires a different mode of thought, and tutor and learner may have few mutual points of connection in discovering and understanding the musical drivers, relationships and structures in these works. This article discusses the creation of ‘BitBox!’, a gestural music interface designed to deconstruct and explain the component elements of adaptive composition through interactive play. The interface was displayed at the Dare Protoplay games exposition in Dundee in August 2014. The initial proof-of- concept study proved successful, suggesting possible refinements in design and a broader range of applications.