L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

Griffin, Brian J.; Burken, John J.; Xargay, Enric

doi:10.2514/6.2010-7687

Cited by 13 publications

(9 citation statements)

References 6 publications

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“…The output predictor in Figure 6 represents the desired closed-loop system behavior M ( s ) plus the estimated uncertainties. With incorporation of actuator dynamics in the output predictor 17,26 and delay τ 3 in the control input channel, 27 the output predictor is given by…”

Section: Controller Designmentioning

confidence: 99%

Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control

Zhu

Yin

Chen

et al. 2018

Measurement and Control

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Background: Temperature is one of the main variables need to be regulated in cryogenic wind tunnel to realize the true flight Reynolds number. A new control methodology based on L1 output feedback adaptive control is deployed in the temperature control. Methods: This design is composed of three parts: linear quadratic Gaussian baseline control, L1 adaptive control and nonlinear feedforward control. A linear quadratic Gaussian controller is implemented as the baseline controller to provide the basic robustness of temperature control. A L1 output feedback adaptive controller with a modified piecewise constant adaptive law is deployed as an augmentation for the baseline controller to cancel the uncertainties within the actuator's bandwidth. The modified adaptive law can guarantee better steady-state tracking performance compared with the standard adaptive law. A global nonlinear optimization process is carried out to obtain a suboptimal filter design for the L1 controller to maximize the performance index. The nonlinear feedforward control is to cancel the coupling effects in control of the tunnel. Results: With these design techniques, the augmented L1 adaptive controller improves the performance of the baseline controller in the presence of uncertainties of dynamics. The simulation results and analysis demonstrate the effectiveness of the proposed control architecture. Conclusion: The modification of adaptive law plus the global nonlinear optimization of the filter in the L1 adaptive control architecture helps the controller achieve good control performance and acceptable robustness for the temperature control over a wide range of operations.

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Section: Controller Designmentioning

confidence: 99%

Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control

Zhu

Yin

Chen

et al. 2018

Measurement and Control

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“…When designing the reference system for the statepredictor in (15) the method proposed by [3] is used to design a nominal feedback, K xy , to get the desired response for the nominal linearised model. Compared to using a generic reference system to specify the response, this method takes the cross-coupling effects in the Bmatrix into consideration.…”

Section: Reference System Designmentioning

confidence: 99%

Design and Test of Discrete Time Adaptive Backup Flight Control Laws

Myleus¹,

Simon²,

Rosander³

2014

IFAC Proceedings Volumes

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This paper is the result of a Master Thesis project performed at Saab AB. The main goal of the project was to design and implement a discrete time L 1 adaptive backup controller in pitch to increase performance for an agile fighter aircraft. A lateral controller was also developed as a secondary goal. A discrete time version of the Modified Piecewise Constant L 1 adaptive control formulation was implemented. Results have shown that augmenting a state-feedback controller with an L 1 adaptive controller increases robustness in the whole flying envelope, with satisfactory flying qualities. A switching scheme between two L 1 controllers based on the extension of the landing gear was used to improve the controller performance throughout the whole envelope. The implemented controllers were flown in a simulator with a nonlinear generic fighter aircraft model with promising results.

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“…The first would be the most obvious choice and can be found quite often in literature, see e.g. [11,16,2]. The basic structure is illustrated in Figure 2 Although the approaches differ from each other from a structural point of view, the desired aircraft dynamics to be achieved by the combination of adaptive augmentation and baseline controller in terms of the transfer function α cmd → α remains the same.…”

Section: L1 Adaptive Augmentationmentioning

confidence: 99%

“…A common philosophy is to design a baseline controller, which ensures the desired performance of the nominal aircraft, by application of practical proven techniques (e.g. linear control [2,11,26], nonlinear dynamic inversion [7,22], ...) That way, the existing know-how of the manufacturer in terms of controller design can be fully used. The baseline controller is then augmented by an adaptive controller, which significantly contributes to the total control signal only in case of an existing deficiency between a nominal reference model and the actual aircraft response.…”

Section: Introductionmentioning

confidence: 99%

Comparison of L1 Adaptive Augmentation Strategies for a Differential PI Baseline Controller on a Longitudinal F16 Aircraft Model

Hellmundt

Wildschek

Maier

et al. 2015

Advances in Aerospace Guidance, Navigation and Control

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Abstract. In this paper two different approaches are presented to design an adaptive augmentation using L1 Adaptive Control. In terms of reference dynamics, the first one takes the closed-loop aircraft with baseline controller into account. The second approach tries to maintain nominal open-loop aircraft dynamics, with the baseline controller wrapped around the adaptive augmentation. They are compared by application to a model of the longitudinal dynamics of a F16 aircraft. The aircraft model is equipped with a Differential PI (DPI) baseline controller. The design of the combination of baseline controller and augmentation takes saturation as well as rate limitation of the control signal directly into account. Simulation results show the nominal closed-loop behavior is not harmed by the adaptive augmentation and that an increase of performance in case of uncertainty can be achieved. As an exemplary uncertainty case a rapid shift of the center of gravity (CG) is examined. The robustness of the controller structure is assessed by the use of both linear and nonlinear methods to obtain the Time Delay Margin (TDM) and the Gain Margin (GM) of the closed loop system. It can be observed, the adaptive augmentation leads to a significant decrease of robustness w.r.t. the plant input channel. This drop in TDM and GM can be fully restored by the application of a hedging strategy.

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L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

Cited by 13 publications

References 6 publications

Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control

Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control

Design and Test of Discrete Time Adaptive Backup Flight Control Laws

Comparison of L1 Adaptive Augmentation Strategies for a Differential PI Baseline Controller on a Longitudinal F16 Aircraft Model

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L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

Cited by 13 publications

References 6 publications

Temperature control of cryogenic wind tunnel with a modified L1 adaptive output feedback control

Temperature control of cryogenic wind tunnel with a modified L1 adaptive output feedback control

Design and Test of Discrete Time Adaptive Backup Flight Control Laws

Comparison of L1 Adaptive Augmentation Strategies for a Differential PI Baseline Controller on a Longitudinal F16 Aircraft Model

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Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control

Temperature control of cryogenic wind tunnel with a modified L₁ adaptive output feedback control