An LFT approach to robust gain scheduling

Magni, J. F.

doi:10.1109/cdc.2005.1583451

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…The first issue is to design a gain‐scheduled LFT controller, ie, a static LFT gain K ( θ ) placing closed‐loop poles for the open‐loop plant model G ( s , θ ), using the technique in the aforementioned work . All θ ‐dependent quantities in the following Lemma are supposed to be under an LFT form.…”

Section: Gain‐scheduling and Robustness Toolsmentioning

confidence: 99%

“…Following the aforementioned work, an open‐loop LFT model under form is built using the LFR Toolbox, with input u , outputs z and q , and states α and q . The parameters of the LFT model are Z α , M α , and M q , whose ranges of variation correspond to the set of 214 linearized models.…”

Section: Design and Validation Of A Gain‐scheduled Flight Controllermentioning

confidence: 99%

“…Several gain‐scheduling state‐space control design techniques can be used, which assume time‐varying or time‐invariant scheduling parameters, see the work of Rugh and Schamma for a survey. In the sequel, we will focus on the modal technique in the work of Magni because this one appears especially suitable for aeronautical applications: a static output feedback controller placing the main closed‐loop poles is synthesized under an LFT form. It only depends on the main A/C parameters to minimize online complexity and to avoid an unsatisfactory transient response of the adaptive closed loop.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive LFT control of a civil aircraft with online frequency‐domain parameter estimation

Ferreres

Hardier²

2017

Intl J Robust & Nonlinear

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Summary This paper describes the application of an indirect linear fractional transformation (LFT)–based state‐space adaptive control scheme to a transport aircraft, within the context of the European project REconfiguration of CONtrol in Flight for Integral Global Upset REcovery. The principle of the scheme is to design and validate off‐line a gain‐scheduled controller, depending on the plant parameters to be estimated, and to combine it online with a model estimator, so as to minimize the onboard computational time and complexity. A modal approach, very classical for the design of a flight control law, is used to directly synthesize the static output feedback LFT controller, depending on the control and stability derivatives, ie, the parameters of the linearized aerodynamic state‐space model to be estimated. Since the gain‐scheduled LFT controller online depends on the parameter estimates instead of the true values, its robustness to transient and asymptotic estimation errors needs to be assessed using μ and integral quadratic constraint analysis techniques. A primary concern being an online implementation, a fully recursive frequency‐domain estimation technique is proposed, with a low online computational burden and the capability to track time‐varying parameters. Full nonlinear simulations along a trajectory validate the good performance properties of the combined estimator and gain‐scheduled flight controller. To some extent, minimal guaranteed stability and performance properties of the adaptive scheme can be ensured by switching to a robust controller when the parameter estimates are not reliable enough, thus bypassing the Certainty Equivalence Principle.

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Section: Gain‐scheduling and Robustness Toolsmentioning

confidence: 99%

Section: Design and Validation Of A Gain‐scheduled Flight Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive LFT control of a civil aircraft with online frequency‐domain parameter estimation

Ferreres

Hardier²

2017

Intl J Robust & Nonlinear

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“…Other representations may assume polynomial dependency, even rational ones. The specific class of Linear Fractional Representation of LPV systems [55], [56] allows to deal with all the previous cases which is very useful in practical applications [57].…”

Section: An Lpv Approach For Ftcmentioning

confidence: 99%

LPV methods for fault-tolerant vehicle dynamic control

Sename

Tudón-Martínez

Fergani

2013

2013 Conference on Control and Fault-Tolerant Systems (SysTol)

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This paper aims at presenting the interest of the Linear Parameter Varying (LPV) methods for vehicle dynamics control, in particular when some actuators may be in failure. The cases of the semi-active suspension control problem and the yaw control using braking, steering and suspension actuators will be presented. In the first part, we will consider the semi-active suspension control problem, where some sensors or actuator (damper leakage) faults are considered. From a quarter-car vehicle model including a non linear semi-active damper model, an LPV model will be described, accounting for some actuator fault represented as some varying parameters. A single LPV fault-tolerant control approach is then developed to manage the system performances and constraints. In the second part the synthesis of a robust gain-scheduled H∞ vehicle dynamic stability controller, involving front steering, rear braking, and four active suspension actuators, is proposed to improve the yaw stability and lateral performances. An original LPV method for actuator coordination is proposed, when the actuator limitations and eventually failures, are taken into account. Some simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations (in particular a loss of some actuator), show the efficiency and robustness of the proposed solution.

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