To accelerate aircraft conception and reduce development costs, computer-aided preliminary design is widely used (e.g., for controller design, performance analysis etc.). The computer-based approach has been rendered possible thanks to advances in modeling tools, allowing to faithfully reproduce complex physical phenomena with limited - expensive - experimental tests. Due to these economical considerations and technological advances, aeronautical control engineers can rely and work with a considerable amount of very accurate models. The counterpart of this accuracy is the resulting numerical complexity which leads (i) to a prohibitively large number of variables to manage, rendering the control design task very complex (i.e., numerical tools become nearly inefficient), and (ii) to models with an accuracy level too high for the control synthesis purpose (indeed modern control techniques usually require low-order representations). In this chapter, based on multiple initial large-scale linear time invariant models, the problem of constructing a suitable low-order parameter dependent model, appropriate to the control design purpose, is addressed. The proposed solution is illustrated on a complex generic Business Jet (BizJet) aeroelastic control-design problem.

Chapter Contents:

• Abstract
• 11.1 Introduction
• 11.1.1 Foreword on the Dassault-Aviation BizJet models
• 11.1.2 The BizJet aircraft aeroelatic control problem
• 11.1.3 Mathematical problem formulation
• 11.1.4 Structure and notation
• 11.2 Multi-LTI model approximation and interpolation algorithm overview
• 11.3 Frequency-limited large-scale MIMO multi-LTI models approximation
• 11.3.1 Preliminaries on projection-based LTI model approximation
• 11.3.2 Large-scale single-LTI model approximation procedure
• 11.3.3 Large-scale multi-LTI models approximation procedure
• 11.3.4 Application to the BizJet model
• 11.4 Interpolation of the reduced-order models
• 11.4.1 Choice of a suitable state-space form
• 11.4.2 Description of the interpolation method
• 11.4.3 Generation of a simplified LFR
• 11.4.4 Application to the BizJet model
• 11.5 Conclusion
• Acknowledgments
• References

Inspec keywords: computational complexity; large-scale systems; cost reduction; control system synthesis; aircraft control

Other keywords: large-scale linear time invariant model; development cost reduction; computer-aided preliminary design; aeronautical control engineer; control-oriented aeroelastic BizJet low-order LFT modeling; control synthesis purpose; BizJet aeroelastic control-design problem; numerical complexity; control techniques; complex physical phenomena; aircraft conception; complex generic Business Jet; modeling tool; low-order parameter dependent model; computer-based approach; control design task; control design purpose

Subjects: Multivariable control systems; Aerospace control; Computational complexity; Control system analysis and synthesis methods