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Hunt, L. R.

Publications and source records attributed to Hunt, L. R..

At least 19 records

Nonlinear system guidance in the presence of transmission zero dynamics

An iterative procedure is proposed for computing the commanded state trajectories and controls that guide a possibly multiaxis, time-varying, nonlinear system with transmission zero dynamics through a given arbitrary sequence of control points. The procedure is initialized by the system inverse with the transmission zero effects nulled out. Then the 'steady state' solution of the perturbation model with the transmission zero dynamics intact is computed and used to correct the initial zero-free solution. Both time domain and frequency domain methods are presented for computing the steady state solutions of the possibly nonminimum phase transmission zero dynamics. The procedure is illustrated by means of linear and nonlinear examples.

Meyer, G.

Identification of nonlinear systems

Given a Volterra series representations of an input-output system, the authors present a result concerning conditions under which there exists a feedback linearizable realization of the nonlinear system. In addition, they have developed a method to compute the unknown parameters in a canonical form realization from the known Volterra kernels. A finite number of parameters can be calculated from an associated finite number of the kernels. The authors restrict themselves to single-input, single-output continuous-time systems. It is assumed that the systems have real analytic state-space representations. The realization results are local, taking place a neighborhood of the origin in state space.

Hunt, L. R.

Applications of nonlinear systems theory to control design

For most applications in the control area, the standard practice is to approximate a nonlinear mathematical model by a linear system. Since the feedback linearizable systems contain linear systems as a subclass, the procedure of approximating a nonlinear system by a feedback linearizable one is examined. Because many physical plants (e.g., aircraft at the NASA Ames Research Center) have mathematical models which are close to feedback linearizable systems, such approximations are certainly justified. Results and techniques are introduced for measuring the gap between the model and its truncated linearizable part. The topic of pure feedback systems is important to the study.

Hunt, L. R.

Unmodeled dynamics and nonlinear control: Wrapup

Theoretical and applicable results concerning systems of nonlinear ordinary differential equations and control of partial differential equations are examined. Titles and abstracts of recent papers are presented.

Hunt, L. R.

Canonical coordinates for partial differential equations

Necessary and sufficient conditions are found under which operators of the form Sigma (m, j=1) x (2) sub j + X sub O can be made constant coefficient. In addition, necessary and sufficient conditions are derived which classify those linear partial differential operators that can be moved to the Kolmogorov type.

Hunt, L. R.

Parallels between control PDE's and systems of ODE's

System theorists understand that the same mathematical objects which determine controllability for nonlinear control systems of ordinary differential equations (ODEs) also determine hypoellipticity for linear partial differential equations (PDEs). Moreover, almost any study of ODE systems begins with linear systems. It is remarkable that Hormander's paper on hypoellipticity of second order linear p.d.e.'s starts with equations due to Kolmogorov, which are shown to be analogous to the linear PDEs. Eigenvalue placement by state feedback for a controllable linear system can be paralled for a Kolmogorov equation if an appropriate type of feedback is introduced. Results concerning transformations of nonlinear systems to linear systems are similar to results for transforming a linear PDE to a Kolmogorov equation.

Hunt, L. R.

Applications of nonlinear systems theory to control design

For most applications in the control area, the standard practice is to approximate a nonlinear mathematical model by a linear system. Since the feedback linearizable systems contain linear systems as a subclass, the procedure of approximating a nonlinear system by a feedback linearizable one is examined. Because many physical plants (e.g., aircraft at the NASA Ames Research Center) have mathematical models which are close to feedback linearizable systems, such approximations are certainly justified. Results and techniques are introduced for measuring the gap between the model and its truncated linearizable part. The topic of pure feedback systems is important to the study.

Hunt, L. R.

Nonlinear filter design

A technique for identifying nonlinear systems was introduced, beginning with a single input-single output system. Assuming the system is initially at rest, the first kernel (first convolution integral in the continuous case or first convolution sum in the discrete case) was calculated. A controllable and observable linear realization was then obtained in a particular canonical form. The actual nonlinear system was probed with an appropriate input (or inputs) and the output (or outputs) determined. For the linear system, the input was computed that produces the same output. In the difference between the inputs to the nonlinear and linear systems, basic information was found about the nonlinear system. There is an interesting class of nonlinear systems for which this type of identification scheme should prove to be accurate.

Hunt, L. R.

Parallels between control PDE's (Partial Differential Equations) and systems of ODE's (Ordinary Differential Equations)

System theorists understand that the same mathematical objects which determine controllability for nonlinear control systems of ordinary differential equations (ODEs) also determine hypoellipticity for linear partial differentail equations (PDEs). Moreover, almost any study of ODE systems begins with linear systems. It is remarkable that Hormander's paper on hypoellipticity of second order linear p.d.e.'s starts with equations due to Kolmogorov, which are shown to be analogous to the linear PDEs. Eigenvalue placement by state feedback for a controllable linear system can be paralleled for a Kolmogorov equation if an appropriate type of feedback is introduced. Results concerning transformations of nonlinear systems to linear systems are similar to results for transforming a linear PDE to a Kolmogorov equation.

Hunt, L. R.

Canonical coordinates for partial differential equations

Necessary and sufficient conditions are found under which operators of the form Sigma(m, j=1) X(2)sub j + X sub 0 can be made constant coefficient. In addition, necessary and sufficient conditions are derived which classify those linear partial differential operators that can be moved to the Kolmogorov type.

Hunt, L. R.

Nonlinear input-output systems

Necessary and sufficient conditions that the nonlinear system dot-x = f(x) + ug(x) and y = h(x) be locally feedback equivalent to the controllable linear system dot-xi = A xi + bv and y = C xi having linear output are found. Only the single input and single output case is considered, however, the results generalize to multi-input and multi-output systems.

Hunt, L. R.

Nonlinear system approximations

The approximation of a nonlinear system by a feedback linearizable system instead of a linear system is considered. Two approaches presently exist in the literature. One involves the concept of involutivity to a certain order, and the other considers a canonical expansion and pure feedback approximation. The relationship between these two methods is shown. This provides insight into lower-order invariants in the equivalence problem for two nonlinear systems. The output time responses for a nonlinear system and its feedback linearizable approximation are outlined.

Goldthwait, Richard G.

Aerothermal tests of spherical dome protuberances on a flat plate at a Mach number of 6.5

Aerothermal tests were conducted in the Langley 8-Foot High-Temperature Tunnel at a Mach number of 6.5 on a series of spherical dome protuberances mounted on a flat-plate test apparatus. Detailed surface pressure and heating-rate distributions were obtained for various dome heights and diameters submerged in both laminar and turbulent boundary layers including a baseline geometric condition representing a thermally bowed metallic thermal protection system (TPS) tile. The present results indicated that the surface pressures on the domes were increased on the windward surface and reduced on the leeward surface as predicted by linearized small-perturbation theory, and the distributions were only moderately affected by boundary-layer variations. Surface heating rates for turbulent flow increased on the windward surface and decreased on the leeward surface similar to the pressure; but for laminar boundary layers, the heating rates remained high on the leeward surface, probably due to local transition. Transitional flow effects cause heat load augmentation to increase by 30 percent for the maximum dome height in a laminar boundary layer. However, the corresponding augmentation for a dome with a height of 0.1 in. and a diameter of 14 in. representative of a bowed TPS tile was 14 percent or less for either a laminar or turbulent boundary layer.

Glass, C. E.

A canonical expansion for nonlinear systems

The importance of differential geometry, particularly Lie brackets of vector fields, in the study of nonlinear systems is well established. Under very mild assumptions, it is shown that a real-analytic nonlinear system has an expansion in which the coefficients are computed in terms of Lie brackets. This expansion occurs in a special coordinate system. The concept of a pure feedback system is also explained. For control design involving a nonlinear system, one approach is to put the system in its canonical expansion and approximate by that part having only feedback paths.

Su, R.

A simple algorithm for computing canonical forms

It is well known that all linear time-invariant controllable systems can be transformed to Brunovsky canonical form by a transformation consisting only of coordinate changes and linear feedback. However, the actual procedures for doing this have tended to be overly complex. The technique introduced here is envisioned as an on-line procedure and is inspired by George Meyer's tangent model for nonlinear systems. The process utilizes Meyer's block triangular form as an intermedicate step in going to Brunovsky form. The method also involves orthogonal matrices, thus eliminating the need for the computation of matrix inverses. In addition, the Kronecker indices can be computed as a by-product of this transformation so it is necessary to know them in advance.

Ford, H.

Approximating linearizations for nonlinear systems

The following problem is examined: given a nonlinear control system dot-x(t) = f(x(t)) + the sum to m terms(i=1) u sub i (t)g sub i (x(t)) on R(n) and a point x(0) in R(n), approximate the system near x(0) by a linear system. One approach is to use the usual Taylor series linearization. However, the controllability properties of both the nonlinear and linear systems depend on certain Lie brackets of the vector field under consideration. This suggests that a linear approximation based on Lie bracket matching should be constructed at x(0). In general, the linearizations based on the Taylor method and the Lie bracket approach are different. However, under certain mild assumptions, it is shown that there is a coordinate system for R(n) near x(0) in which these two types of linearizations agree. The importance of this agreement is indicated by examining the time responses of the nonlinear system and its linear approximation and comparing the lower order kernels in Volterra expansions of each.

Hunt, L. R.

A canonical form for nonlinear systems

The concepts of transformation and canonical form have been used in analyzing linear systems. These ideas are extended to nonlinear systems. A coordinate system and a corresponding canonical form are developed for general nonlinear control systems. Their usefulness is demonstrated by showing that every feedback linearizable system becomes a system with only feedback paths in the canonical form. For control design involving a nonlinear system, one approach is to put the system in its canonical form and approximate by that part having only feedback paths.

Su, R.