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Results for “parameter-varying control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Linear Parameter-Varying Control Compatible with Excitation for Real-Time Modeling

The Modeling and Control for Agile Aircraft Development project (MCAAD) seeks to reduce the time spent on wind tunnel testing and computational fluid dynamic modeling when developing control laws for new commercial and military aircraft. MCAAD uses advanced dynamic modeling procedures coupled with real-time control design which can reduce the time and cost spent on traditional aircraft development methods. This is done in-flight by using a real-time modeling procedure where programmed test inputs (PTI) deflect the aircraft control surfaces, and the responses are measured in order to create a dynamic model. This paper presents an 𝐻∞-based linear parameter-varying (LPV) control law designed on a nonlinear rigid-body dynamic model which commands control surface deflections at frequencies above the PTI frequency band. Thus the controller will not suppress the response due to the PTI. The LPV controller is compared with a previously designed Nonlinear Dynamic Inversion (NDI) controller and the coherence between the commanded control surface deflections and the PTI is plotted for both controllers. The LPV controller is shown to distort the PTI less than the NDI controller.

Luke J. Miller↗
NASA NTRS2002

LPV Controller Interpolation for Improved Gain-Scheduling Control Performance

In this paper, a new gain-scheduling control design approach is proposed by combining LPV (linear parameter-varying) control theory with interpolation techniques. The improvement of gain-scheduled controllers can be achieved from local synthesis of Lyapunov functions and continuous construction of a global Lyapunov function by interpolation. It has been shown that this combined LPV control design scheme is capable of improving closed-loop performance derived from local performance improvement. The gain of the LPV controller will also change continuously across parameter space. The advantages of the newly proposed LPV control is demonstrated through a detailed AMB controller design example.

Wu, Fen↗
NASA NTRS2017

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

LPV Modeling↗
NASA NTRS1991

Guaranteed properties of gain scheduled control for linear parameter-varying plants

Gain scheduling has proven to be a successful design methodology in many engineering applications. However, in the absence of a sound theoretical analysis, these designs come with no guarantees on the robustness, performance, or even nominal stability of the overall gain scheduled design. This paper presents such an analysis for one type of gain scheduled system, namely, a linear parameter-varying plant scheduling on its exogenous parameters. Conditions are given which guarantee that the stability, robustness, and performance properties of the fixed operating point designs carry over to the global gain scheduled design. These conditions confirm and formalize popular notions regarding gain scheduled design, such as the scheduling variable should 'vary slowly'.

Shamma, Jeff S.↗
NASA NTRS2007

Robust Gain-Scheduled Fault Tolerant Control for a Transport Aircraft

This paper presents an application of robust gain-scheduled control concepts using a linear parameter-varying (LPV) control synthesis method to design fault tolerant controllers for a civil transport aircraft. To apply the robust LPV control synthesis method, the nonlinear dynamics must be represented by an LPV model, which is developed using the function substitution method over the entire flight envelope. The developed LPV model associated with the aerodynamic coefficient uncertainties represents nonlinear dynamics including those outside the equilibrium manifold. Passive and active fault tolerant controllers (FTC) are designed for the longitudinal dynamics of the Boeing 747-100/200 aircraft in the presence of elevator failure. Both FTC laws are evaluated in the full nonlinear aircraft simulation in the presence of the elevator fault and the results are compared to show pros and cons of each control law.

Shin, Jong-Yeob↗
NASA NTRS2004

Switching LPV Control for High Performance Tactical Aircraft

This paper examines a switching Linear Parameter-Varying (LPV) control approach to determine if it is practical to use for flight control designs within a wide angle of attack region. The approach is based on multiple parameter-dependent Lyapunov functions. The full parameter space is partitioned into overlapping subspaces and a family of LPV controllers are designed, each suitable for a specific parameter subspace. The hysteresis switching logic is used to accomplish the transition among different parameter subspaces. The proposed switching LPV control scheme is applied to an F-16 aircraft model with different actuator dynamics in low and high angle of attack regions. The nonlinear simulation results show that the aircraft performs well when switching among different angle of attack regions.

Lu, Bei↗
NASA NTRS2001

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

Garrard, William L.↗
NASA NTRS2003

LPV Antiwindup Compensation for Enhanced Flight Control Performance

In this paper, we propose a saturation control scheme for linear parameter-varying (LPV) systems from an antiwindup control perspective. The proposed control approach is advantageous because it can be thought of as an augmented control algorithm from the existing control system. Moreover, the synthesis condition for an antiwindup compensator is formulated as a linear matrix inequality (LMI) optimization problem and can be solved efficiently. We have applied the LPV antiwindup controller to an F-16 longitudinal autopilot control system design to enhance aircraft safety and improve flight quality in a high angle of attack region.

Lu, Bei↗
NASA NTRS2018

Wing Shaping and Gust Load Controls of Flexible Aircraft: An LPV Approach

In the proposed paper, the optimum wing shape of a highly flexible aircraft under varying flight conditions will be controlled by a linear parameter-varying approach. The optimum shape determined under multiple objectives, including flight performance, ride quality, and control effort, will be determined as well. This work is an extension of work done previously by the authors, and updates the existing optimization and utilizes the results to generate a robust flight controller.

Gust Load Alleviation↗
NASA NTRS2006

Rate-Based Model Predictive Control of Turbofan Engine Clearance

An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

DeCastro, Jonathan A.↗
NASA NTRS2004

Switching LPV Control of an F-16 Aircraft via Controller State Reset

In flight control, the design objective and the aircraft dynamics may be different in low and high angle of attack regions. This paper presents a systematic switching Linear Parameter-varying LPV method to determine if it is practical to use for flight control designs over a wide angle of attack region. The approach is based on multiple parameter-dependent Lyapunov functions a family of LPV controllers are designed, and each of them is suitable for a specific parameter subspace. The state of the controller is reset to guarantee the stability requirement of the Lyapunov function when the switching event occurs. Two parameter-dependent switching logics, hysteresis switching and switching with average dwell times are examined. The proposed switching LPV control scheme is applied to an F-16 aircraft model with different design objectives and aircraft dynamics in low and high angle of attack regions. The nonlinear simulating results using both switching logics are compared.

Lu, Bei↗
NASA NTRS2017

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi↗
NASA NTRS2000

Parametric Modeling and Fault Tolerant Control

Fault tolerant control is considered for a nonlinear aircraft model expressed as a linear parameter-varying system. By proper parameterization of foreseeable faults, the linear parameter-varying system can include fault effects as additional varying parameters. A recently developed technique in fault effect parameter estimation allows us to assume that estimates of the fault effect parameters are available on-line. Reconfigurability is calculated for this model with respect to the loss of control effectiveness to assess the potentiality of the model to tolerate such losses prior to control design. The control design is carried out by applying a polytopic method to the aircraft model. An error bound on fault effect parameter estimation is provided, within which the Lyapunov stability of the closed-loop system is robust. Our simulation results show that as long as the fault parameter estimates are sufficiently accurate, the polytopic controller can provide satisfactory fault-tolerance.

Wu, N. Eva↗
NASA NTRS2016

Model Order Reduction of Aeroservoelastic Model of Flexible Aircraft

This paper presents a holistic model order reduction (MOR) methodology and framework that integrates key technological elements of sequential model reduction, consistent model representation, and model interpolation for constructing high-quality linear parameter-varying (LPV) aeroservoelastic (ASE) reduced order models (ROMs) of flexible aircraft. The sequential MOR encapsulates a suite of reduction techniques, such as truncation and residualization, modal reduction, and balanced realization and truncation to achieve optimal ROMs at grid points across the flight envelope. The consistence in state representation among local ROMs is obtained by the novel method of common subspace reprojection. Model interpolation is then exploited to stitch ROMs at grid points to build a global LPV ASE ROM feasible to arbitrary flight condition. The MOR method is applied to the X-56A MUTT vehicle with flexible wing being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies demonstrated that relative to the fullorder model, our X-56A ROM can accurately and reliably capture vehicles dynamics at various flight conditions in the target frequency regime while the number of states in ROM can be reduced by 10X (from 180 to 19), and hence, holds great promise for robust ASE controller synthesis and novel vehicle design.

aeroelasticity↗
NASA NTRS2018

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗