Understandings of Classical and Incremental Backstepping Controllers With Model Uncertainties

Jeon, Byoung-Ju; Seo, Min-Guk; Shin, Hyo‐Sang; Tsourdos, Antonios

doi:10.1109/taes.2019.2952631

Cited by 13 publications

(13 citation statements)

References 28 publications

(48 reference statements)

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“…where ‖ • ‖ is a norm in a space of functions of inputs 𝑥. If the norm is defined via the inner product of the reproducing kernel Hilbert space (RKHS) generated by the kernel 𝐾 0 , then minimising (26), one can obtain the followin g expression…”

Section: A Online Learningmentioning

confidence: 99%

“…When the mismatch between the real and model control efficiency is constant, i.e. when the system input affine property is conserved, the IBKS is able to cancel the produced uncertainty [22,26,43]. Nevertheless, the developed on-line estimations of control effectiveness could improve the control quality.…”

Section: Fig2 Two Failures and Loss Of Effectivenessmentioning

confidence: 99%

“…[23,24]. Regardless of the fact that IBKS 2 demonstrates robustness to some failures [25,26] estimation of the control effectiveness improves fault-tolerant abilities of the system [22,[27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Gaussian Process Adaptive Incremental Backstepping Flight Control

Ignatyev

Shin

Tsourdos

2022

AIAA SCITECH 2022 Forum

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The presence of uncertainties caused by unforeseen malfunctions in the actuation system or changes in aircraft behaviour could lead to aircraft loss of control during flight. The paper proposes almost model-independent control law combining recent developments in nonlinear control theory, data-driven methods, and sensor technologies by considering Gaussian Processes Adaptive augmentation for Incremental Backstepping control (IBKS) algorithm. IBKS uses angular accelerations and current control deflections to reduce the dependency on the aircraft model. However, it requires knowledge of control effectiveness. Conducted research shows that if the input-affine property of the IBKS is violated, e.g., in severe conditions with a combination of multiple failures, the IBKS can lose stability. Meanwhile, the GP-based estimator provides fast identification and the resultant GP-adaptive IBKS algorithm demonstrates improved stability and tracking performance. The performance of the algorithm is validated using a large transport aircraft flight dynamics model.

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Section: A Online Learningmentioning

confidence: 99%

Section: Fig2 Two Failures and Loss Of Effectivenessmentioning

confidence: 99%

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Gaussian Process Adaptive Incremental Backstepping Flight Control

Ignatyev

Shin

Tsourdos

2022

AIAA SCITECH 2022 Forum

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“…The only model information that IB requires is control effectiveness. Recent studies [19][20][21] have found a condition under which the stability of the IB-controlled system will not be degraded by the uncertainties in control effectiveness; by increasing the sample rate, the effect of uncertainty in control effectiveness can be largely attenuated. Generally, IB obtains control effectiveness through numerical differentiation of aerodynamic data.…”

Section: Introductionmentioning

confidence: 99%

Incremental Backstepping Sliding-Mode Trajectory Control for Tailless Aircraft with Stability Enhancer

Wang

et al. 2022

Aerospace

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This paper presents an incremental backstepping sliding-mode (IBS) controller for trajectory control of a tailless aircraft with unknown disturbances and model uncertainties. The proposed controller is based on a nonlinear dynamic model of the tailless aircraft. A stability enhancer (SE) that limits both the rate and amplitude of the virtual control input is proposed. The stability enhancer consists of two layers. When the virtual control input approaches the edge, the first layer SE would be activated to modify the trajectory tracking error; when the virtual control input exceeds the edge, the second layer SE would reduce the control gains to make sure the virtual control input drops within the edge as soon as possible. With the help of SE, the incremental control method could be extended to outer-loop control without considering the dynamics of the inner-loop system. In addition, an adaptive estimator for state derivatives is proposed, together with IBS, allowing the controller to show excellent robustness. Finally, two simulations are presented. The first simulation shows that the system is insensitive to external disturbances and model uncertainties, and the effectiveness of SE is proved in the second simulation.

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“…The ability of BC to cope with the change in structural parameters is enhanced in Lu et al (2015) by adjusting the control parameters. In Jeon et al (2020), it is further pointed out that the selection of the control parameters in BC should consider the range of the uncertain parameters. The control parameters of BC are optimized and determined in Yu et al (2016) by the differential evolution algorithm.…”

Section: Introductionmentioning

confidence: 99%

Power Coordinated Control and Parameter Analysis for Spiral Spring Energy Storage Systems Based on Backstepping Control Under Current Vector Orientation

Wang

Zhang

et al. 2022

Front. Energy Res.

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As a new and great source of potential energy storage technology, the spiral spring energy storage (SSES) technology uses a permanent magnet synchronous machine (PMSM) to tighten or release the spiral spring for energy conversion. In allusion to the feature of simultaneous variations in torque and inertia for spiral springs in operation, it is difficult for the SSES system to show good control performance in regulating the power from/to the grid under a conventional vector control method. A power coordinated control scheme of the SSES system with the grid is proposed to integrate the grid-side converter (GSC) with the machine-side converter (MSC) based on backstepping control under the current vector orientation. First, the mathematical models of GSC and PMSM under the current vector orientation coordinate frame are established. Second, the coordinated control scheme is designed by the backstepping control principle, and its stability is proved in theory. Then, the optimal control parameters in the control scheme are determined by investigating the desired control performance. Ultimately, the simulation and experimental results show that the proposed control scheme with the chosen control parameters coordinates the GSC and the MSC well. The power signal is tracked accurately and rapidly, and the operation performance of the SSES system and its energy exchange with the grid are both improved effectively.

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Understandings of Classical and Incremental Backstepping Controllers With Model Uncertainties

Cited by 13 publications

References 28 publications

Gaussian Process Adaptive Incremental Backstepping Flight Control

Gaussian Process Adaptive Incremental Backstepping Flight Control

Incremental Backstepping Sliding-Mode Trajectory Control for Tailless Aircraft with Stability Enhancer

Power Coordinated Control and Parameter Analysis for Spiral Spring Energy Storage Systems Based on Backstepping Control Under Current Vector Orientation

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