Robust Continuous Finite-Time Control of a Helicopter in Turbulence

Halbe, Omkar; Oza, Harshal B.

doi:10.1109/lcsys.2020.2999307

Cited by 12 publications

(10 citation statements)

References 23 publications

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“…rsion December 18, 2021 submitted to Aerospace 4 of 17 The uncertainty f : R 4 × R + → R 8 represents bounded turbulence acting on the input channels (matched uncertainty), i.e., f = Bδu, where δu ≡ δD θ δD α δD β δD δ ∈ R 4 is the plant input disturbance due to turbulence. Turbulence is simulated by an empirical control equivalent turbulence input (CETI) model that uses filters driven by zero mean, unity covariance, band-limited white noise (W n ) [20,27]:…”

Section: Model Descriptionmentioning

confidence: 99%

“…The response requirement implies that the system states must converge and obey the closed-loop behavior specified in Equations ( 3)-( 6). This requirement motivates the choice of the sliding variable, since by definition the sliding variable shall represent a stable manifold in the system's state space [17,20]:…”

Section: Sliding Manifoldmentioning

confidence: 99%

“…The SOSM approach offers a continuous control signal (instead of a discontinuous one) without compromising the robustness properties of SMC [19]. One of the first SOSM helicopter flight controllers in Reference [20] showed robustness to both matched and unmatched perturbations. However, its design assumed input decoupling in an essentially highly-coupled, multi-input, multi-output plant, and it necessitated an observer to estimate the sliding variable derivative.…”

Section: Introductionmentioning

confidence: 99%

“…Its multivariable structure respects plant cross-coupling and ensures an identical convergence time for all sliding variables. Unlike References [9,20], estimation of neither the sliding variable derivative nor the exogenous disturbance input is needed, thus offering a simpler yet equally robust controller.…”

Section: Introductionmentioning

confidence: 99%

“…To our best knowledge, this constitutes the first SOSM controller validation on a nonlinear helicopter plant, since Reference [20] used a lower-order, linear plant. Performance comparisons are also presented between the STFC and a linear quadratic flight controller, the latter synthesized along the lines of Reference [24].…”

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confidence: 99%

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A Continuous Multivariable Finite-Time Super-Twisting Attitude and Rate Controller for Improved Rotorcraft Handling

Halbe

Hajek

2021

Aerospace

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This paper synthesizes a continuous, multivariable, finite-time-convergent, super-twisting attitude and rate controller for rotorcraft with the objective of providing desired handling qualities and robustness characteristics. A sliding manifold is defined in the system state space to represent ideal attitude and rate command response dynamics of relative degree one with respect to the command input. Subsequently, robust command tracking is achieved via the synthesis of a multivariable super-twisting flight controller, which renders the plant states convergent on to the defined sliding manifold in finite-time and in the presence of matched external disturbance input. To validate the efficacy of the controller, simulation results are presented based on a nonlinear, higher-order rotorcraft model operating in turbulence. True system convergence to the sliding manifold from an untrimmed state is shown to lie within the theoretically predicted finite-time convergence bound. Furthermore, simulations with a linear quadratic flight controller are also presented for performance comparison with the proposed super-twisting flight controller.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Sliding Manifoldmentioning

confidence: 99%