T. M. Seigler

Intelligent Control of a Morphing Aircraft

A morphing aircraft is able to drastically alter its planform to optimize performance at very dissimilar flight conditions. Despite significant strides to develop wing structure and actuation systems, much work remains to effectively control both the morphing wing as well as the entire morphing aircraft. The control solution presented in this paper uses modelbased methods that provide precise, closed-loop control of the morphing planform (i.e. wing-shape control) and simultaneously enforce prescribed closed-loop aircraft dynamics (i.e. flight control). The specific planform that is the focus of this research is the N-MAS wing designed by NextGen Aeronautics. At the wing-shape control level, the authors sought to answer two questions: (1) What is the most efficient means of actuating the underlying structure of the N-MAS wing? and (2) Given a fixed set of actuators, how does one precisely manipulate a morphing structure given inherent physical limitations? At the flight-control level, the authors sought to develop a control methodology that can: (1) accommodate different planforms that result in drastically changing plant dynamics, and (2) make the transition between any two configurations while maintaining the stability of the morphing aircraft.

Filtered-dynamic-inversion control for unknown minimum-phase systems with unknown-and-unmeasured disturbances

This article presents a filtered-dynamic-inversion controller for multi-input multi-output linear minimum-phase systems. The controller requires limited model information, specifically, knowledge of the relative degree and the first nonzero Markov parameter. Furthermore, the controller is effective for stabilisation, command following and rejection of unknown-and-unmeasured disturbances. This article analyses the stability and closed-loop performance (i.e. command following error) of filtered dynamic inversion, which is a single-parameter high-parameter-stabilising controller. We show that for sufficiently large parameter the closed-loop is asymptotically stable, and the average power of the performance signal is arbitrarily small.

Distributed Actuation Requirements of Piezoelectric Structures Under Servoconstraints

This article is concerned with the analysis of actuation requirements for dynamic shape control of a piezoelectric structure. A general procedure is given for determining the distributed actuation input required to satisfy a partially specified displacement field for a generic piezoelectric shell structure. It is shown that under certain conditions, a servoconstraint that defines a finite number algebraic relations on the motion of the material points of the structure can be satisfied in steady state by an equivalent number of independent actuators. Application examples are developed to demonstrate application of the theory and its potential usefulness in the analysis and design of advanced engineering structures.

Decentralized Vibration and Shape Control of Structures With Colocated Sensors and Actuators

This paper introduces a decentralized shape and vibration controller for structures with large and potentially unknown system order, model-parameter uncertainty, and unknown disturbances. Controller implementation utilizes distributed, colocated, and independent actuator–sensor pairs. Controller design requires knowledge of the relative degrees of the actuator and sensor dynamics and upper bounds on the diagonal elements of systems high-frequency gain matrix. Closed-loop performance is determined by a parameter gain, which can be viewed as the cutoff frequency of a low-pass filter. For sufficiently large parameter gain, the closed-loop performance is arbitrarily small. Numerical examples are used to demonstrate the application and effectiveness of the decentralized controller, and we present experimental results for a setup consisting of a cantilever beam with piezoelectric actuators and strain-gauge sensors.

A subsystem identification technique for modeling control strategies used by humans

This paper presents evidence in support of the internal model hypothesis of neuroscience. Specifically, we present results from a study that includes 10 human subjects and is designed to explore the internal model hypothesis. A new system identification method is presented for composite systems that include multiple unknown subsystems whose input and output signals may be inaccessible (i.e., unmeasurable). We use this subsystem identification method to model the control strategies that humans employ. In particular, we identify the feedback and feedforward controllers of the subjects in the experiment. The identified controllers suggest that the subjects learned to use inverse plant dynamics in feedforward.

Damping in Periodic Structures: A Continuum Modeling Approach

A homogenized modeling technique is developed in this paper to account for viscous damping properties in beam-like lattice structures of repeated patterns. Necessary assumptions regarding the local free deformations, shear deformation beam theory, and compatibility conditions are made to obtain an equivalent continuum model of a three-dimensional lattice. A dissipated energy equivalence approach is then used to relate the energy dissipation for a general case of damping matrix in a lattice element to an equivalent proportionally damped model. As a result, a continuum model with Kelvin–Voigt damping is obtained. Damped bending natural frequencies, frequency response functions, and damping ratios are found using this method and compared to the results of a finite-element analysis for several structures for the purpose of validation.

Filtered feedback linearization for nonlinear systems with unknown disturbance

Abstract This paper presents a filtered-feedback-linearization controller for multi-input–multi-output nonlinear systems, where the equilibrium of the zero dynamics is locally asymptotically stable. The controller requires limited model information, specifically, knowledge of the vector relative degree and knowledge of the dynamic-inversion matrix, which is the nonlinear extension of the high-frequency-gain matrix for linear systems. Filtered feedback linearization is a single-parameter high-parameter-stabilizing controller, which is effective for command following and rejection of unknown-and-unmeasured disturbances. This paper analyzes the closed-loop stability and performance, that is, the difference between the actual output and an ideal feedback-linearized closed-loop output. We show that for sufficiently small initial conditions and sufficiently large parameter, the state is bounded, and the L ∞ norm of the performance is arbitrarily small.

Frequency-domain observations on how humans learn to control an unknown dynamic system

This paper presents results from an experiment that is designed to explore the approaches that humans use to learn to control an unknown linear time-invariant dynamic system. In this experiment, 10 subjects interacted with an unknown dynamic system 40 times over a 2-week period. We use subsystem identification to model the control strategies that the subjects employ on each of their 40 trials. In particular, we estimate feedback and feedforward controllers used by each subject on each trial. The controllers identified on the 40th trial suggest that the subjects learned to use the inverse plant dynamics in feedforward. Moreover, the identified feedforward controllers converge to the approximate inverse dynamics in fewer trials (i.e., more quickly) at middle frequencies than at low and high frequencies.

Decentralized filtered dynamic inversion for uncertain minimum-phase systems

Decentralized filtered dynamic inversion is a control method for uncertain linear time-invariant systems that are minimum phase, have multi-input multi-output decentralized subsystems, and are potentially subject to unknown disturbances. This controller requires limited model information, specifically, knowledge of the relative degree and an estimate of the first nonzero Markov parameter for each local subsystem. Decentralized filtered dynamic inversion is effective for command following and rejection of unknown disturbances. We derive the decentralized filtered-dynamic-inversion controller and analyzes the closed-loop stability and performance (i.e., command-following error). We show that for sufficiently large choice of a single control parameter the closed-loop system is asymptotically stable, and the average power of the performance is arbitrarily small.

Dynamic Effects of Embedded Macro-Fiber Composite Actuators on Ultra-Light Flexible Structures of Repeated Pattern- a Homogenization Approach

Motivated by deployable satellite technology, this article presents a homogenization model of an inflatable, rigidized lattice structure with distributed macro-fiber composite (MFC) actuation. The model is based upon a general expression for the strain and kinetic energy of a fundamental repeated element of the structure. These expressions are reduced in order and expressed in terms of the strain and displacement components of an equivalent one-dimensional vibration model. The resulting model is used to analyze changes in the structural natural frequencies introduced by the local effects of the added macro-fiber composite actuators for several configurations. A finite element solution is used as a comparison for the homogenization model, and the two are shown to be in good agreement, although the latter requires significantly less computational effort.