Ricardo S. Sánchez Peña

Modeling and Control of an Aeroelastic Morphing Vehicle

Morphing aircraft are conceived as multirole platforms that modify their external shape substantially to adapt to a changing mission environment The dynamic response of the unmanned aerial vehicle will be governed by the time-varying aerodynamic forces and moments which will be a function of the wings shape changes by the morphing command. Here, it is assumed that the morphing unmanned aerial vehicle behaves as a variable geometry rigid body, but with dynamic coefficients corrected to include quasi-steady aeroelastic effects. A multiloop controller for the aeroelastic morphing unmanned aerial vehicle concept is formulated to provide both proven structural and self-scheduled characteristics. The proposed controller uses a set of inner-loop gains to provide stability using classical techniques, whereas a linear parameter-varying outer-loop controller is devised to guarantee a specific level of robust stability and performance for the time-varying dynamics. Reduced-order controllers are synthesized using a robust control reduction technique. A series of maneuvers are devised to exhaustively evaluate the performance of the synthesized multiloop controller subject to large-scale geometrical shape changes. The underlying multiloop approach successfully enables in-flight transformation between vehicle states in less than one minute, while maintaining the overall vehicle stability and control.

Robust identification with mixed parametric/nonparametric models and time/frequency-domain experiments: theory and an application

We have recently proposed a new robust identification framework, based upon generalized interpolation theory, that allows for combining parametric and nonparametric models and frequency and time-domain experimental data. In this paper we illustrate the advantages of this framework over conventional control oriented identification techniques by considering the problem of identifying a two-degree of freedom structure used as a testbed for demonstrating damage-mitigation and life extension control concepts. This structure is lightly damped, leading to time and frequency domain responses that exhibit large peaks, thus rendering the identification problem nontrivial.

Robust identification of lightly damped flexible structures by means of orthonormal bases

We consider the problem of robust identification of lightly damped flexible structures by means of a family of orthonormal basis functions, in order to model the dynamics of this kind of systems in a certain frequency range of interest. It is possible in this way to reduce conservativeness of the identification process. We propose a method to generate the orthonormal bases that is based on the cascade of balanced state-space realizations of all-pass filters, and develop for this case a less conservative explicit worst case error bounds. We present an application of this method to both simulated and experimental frequency response data.

Practical issues in robust identification

The recent area of robust identification plays an important role in the application of robust control techniques to practical problems. Although the theory has been developed for linear, time invariant, stable plants, in practical applications very seldom we find such classes of systems. To apply these methods in practical situations (possibly nonlinear, time varying and/or unstable plants), the experimental setup should consider the magnitude, duration and maximum frequency of the test signals. >

Robust Identification: An approach to select the class of candidate models

A practical approach to assess the trade-offs in selecting the parameters that define the class of candidate models and that are commonly used in the Robust Identification framework is derived. The procedure minimizes the worst case identification error bound and guarantees consistency, according to all the experimental evidence. A consistency curve is defined, and upper and lower bounds are computed to graphically select these parameters.

An extension of the small gain theorem in ℒ

We consider the class of control systems that consist of a linear time-invariant forward path and a memoryless (possibly time-varying) nonlinear feedback. In this work we extend the small gain theorem in ℒ∞ for these systems, in two ways. On the one hand, we generalize the approach to nonlinearities with bounds of arbitrary shape. On the other hand, we add structure to the analysis, dividing the vectors involved in the problem (outputs, nonlinearities, disturbances) into smaller dimension subvectors. This leads to less conservative conditions in the cases in which some structure of the nonlinearity is known. One important application is to the closed-loop robust stability analysis of a nonlinear plant controlled by a feedback linearizing and stabilizing controller. This is the case of an uncertain nonlinear model to be controlled, affected by measurement noise and external disturbances.