Computational effectiveness of LMI design strategies for vibration control of large structures

Distributed control systems for vibration control of large structures involve a large number of actuation devices and sensors that work coordinately to produce the desired control actions. Design strategies based on linear matrix inequality (LMI) formulations allow obtaining controllers for these complex control problems, which are characterized by large dimensionality, high computational cost and severe information constraints. In this paper, we conduct a comparative study of the computational effectiveness of three different LMI-based controller design strategies: H-infinity, energy-to-peak and energy-to-componentwise-peak. The H-infinity approach is a well-known design methodology and has been widely used in the literature. The energy-to-peak approach is a particular case of generalized H2 design that is gaining a growing relevance in structural vibration control. Finally, the energy-to-componentwise-peak approach is a less common case of generalized H2 design that produces promising results among the three considered approaches. These controller design strategies are applied to synthesize active state-feedback controllers for the seismic protection of a five-story building and a twenty-story building both equipped with complete systems of interstory actuation devices. To evaluate the computational effectiveness of the proposed LMI design methodologies, the corresponding computation times are compared and a suitable set of numerical simulations is carried out to assess the performance of the obtained controllers. As positive results, two main facts can be highlighted: the computational effectiveness of the energy-to-peak control design strategy and the particularly well-balanced behavior exhibited by the energy-to-componentwise-peak controllers. On the negative side, it has to be mentioned the computational inefficiency of the considered LMI design methodologies to properly deal with very-large-scale control problems.Peer ReviewedPostprint (published version

Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations

To perform uncertainty, sensitivity or optimization analysis on scalar variables calculated by a cpu time expensive computer code, a widely accepted methodology consists in first identifying the most influential uncertain inputs (by screening techniques), and then in replacing the cpu time expensive model by a cpu inexpensive mathematical function, called a metamodel. This paper extends this methodology to the functional output case, for instance when the model output variables are curves. The screening approach is based on the analysis of variance and principal component analysis of output curves. The functional metamodeling consists in a curve classification step, a dimension reduction step, then a classical metamodeling step. An industrial nuclear reactor application (dealing with uncertainties in the pressurized thermal shock analysis) illustrates all these steps

Development of an automated aircraft subsystem architecture generation and analysis tool

Purpose – The purpose of this paper is to present a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizers performance with a typical form of application problem. Design/methodology/approach – The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings – Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi-objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research limitations/implications – This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/value – The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods

Fractional robust control of ligthly damped systems

The article proposes a method to design a robust controller ensuring the damping ratio of a closed-loop control. The method uses a contour para-meterized by the damping ratio in the Nichols plane and the complex non-integer (or fractional)differentiation to compute a transfer function whose open-loop Nichols locus tangents this contour, thus ensuring dynamic performance. The proposed method is applied to a flexible structure (a clamped-free beam with piezoelectric ceramics). The aims of the control loop are to decrease the vibrations and to ensure the damping ratio of the controlled system

Topology optimization of multiple anisotropic materials, with application to self-assembling diblock copolymers

We propose a solution strategy for a multimaterial minimum compliance topology optimization problem, which consists in finding the optimal allocation of a finite number of candidate (possibly anisotropic) materials inside a reference domain, with the aim of maximizing the stiffness of the body. As a relevant and novel application we consider the optimization of self-assembled structures obtained by means of diblock copolymers. Such polymers are a class of self-assembling materials which spontaneously synthesize periodic microstructures at the nanoscale, whose anisotropic features can be exploited to build structures with optimal elastic response, resembling biological tissues exhibiting microstructures, such as bones and wood. For this purpose we present a new generalization of the classical Optimality Criteria algorithm to encompass a wider class of problems, where multiple candidate materials are considered, the orientation of the anisotropic materials is optimized, and the elastic properties of the materials are assumed to depend on a scalar parameter, which is optimized simultaneously to the material allocation and orientation. Well-posedness of the optimization problem and well-definition of the presented algorithm are narrowly treated and proved. The capabilities of the proposed method are assessed through several numerical tests

Fractional robust control with iso-damping property

This article deals with the problem of the reduction of structural vibrations with isodamping property. The proposed methodology is based on: - a contour defined in the Nichols plane and significant of the damping ratio of the closed-loop response - a robust control method that uses fractional order integration. The methodology is applied to an aircraft wing model made with a beam and a tank whose different levels of fillings are considered as uncertainties