A New Fast Finite Time Fractional Order Adaptive Sliding-Mode Control for a Quadrotor

Soorki, Mojtaba Naderi; Moghaddam, Tahmine Vedadi; Emamifard, Amin

doi:10.1109/iccia52082.2021.9403563

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…where ϵ and σ are the real and imaginary parts of jω λ , respectively, and θ tp = 0.05. Similarly, the K p and K i equations that were derived for the attitude controllers are given in (36) to (37) (37) From the identified stability boundary surfaces, the optimization constrains which are found to optimize the controller are given in Table 1. Now, using these constrains, the controllers were optimized and the resulting controller parameters which were obtained are given in Table 2.…”

Section: E Quadrotor Controller Tuningmentioning

confidence: 99%

Improved Performance in Quadrotor Trajectory Tracking Using MIMO PI^λ-D Control

et al. 2022

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This paper aims to develop a fractional control approach for quadrotor trajectory tracking. A fractional-order integrator (PI λ ) with a feedback derivative scheme is designed to control each state of the MIMO system. The designed feedback controller stabilizes the initially unstable decoupled states and widens the stability, while PI λ provides precise trajectory tracking capabilities. After a successful simulation study, the new PI λ -D controller is implemented in the hardware environment. The various performance and load disturbance analyses reveal the effectiveness of the proposed scheme compared with the classical PD/PID controllers. The real-time study also shows that this scheme is a simple yet robust solution.

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Section: E Quadrotor Controller Tuningmentioning

confidence: 99%

Improved Performance in Quadrotor Trajectory Tracking Using MIMO PI^λ-D Control

et al. 2022

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“…Second, proving that the defined sliding surface is in such a way that upon

S ((), t)

gets zero and system comes to sliding mode (the sliding phase), the tracking error

e ((), t)

converges to the origin in finite time (let us call this finite time as

T_{e}

). Then, by computing both

T_{s}

and

T_{e}

, one can conclude that the system tracking error will converge to zero in a specified finite time as follows [2,3,4,5]:

T_{finite} goodbreak= T_{s} goodbreak+ T_{e}

…”

Section: Commentsmentioning

confidence: 99%

“…As some examples in other references, in Yu et al [2], a new sliding surface is proposed as

S ((), t) = \overset{\overset{true¯}{q}}{true} ((), t) + α \overset{q}{true} ((), t) + β {|\overset{true¯}{q} (t)|}^{γ} italicsign ((), \overset{q}{true} ((), t))

for

α, β > 0

and

0 < γ < 1

, and it is annalistically shown that for any initial condition

\overset{q}{true} ((), 0)

, system state

\overset{q}{true} ((), t)

will converge to zero in finite time. As another example, in [3,4] a sliding surface is defined as

S ((), t) = \overset{\overset{true¯}{q}}{true} ((), t) + {kD}^{λ - 1} ([], italicsig {(\overset{q}{true})}^{a})

and the authors in [3,4] have done a lot of efforts to analytically show that in sliding phase of system (when

s ((), t) = 0

), the error

\overset{q}{true}

will converge to zero in a finite time like

t = t_{a}

.…”

Section: Commentsmentioning

confidence: 99%

“…Þ for α, β > 0 and 0 < γ < 1, and it is annalistically shown that for any initial condition q 0 ð Þ, system state q t ð Þ will converge to zero in finite time. As another example, in [3,4] a sliding surface is defined as…”

Section: First Main Commentmentioning

confidence: 99%

“…and the authors in [3,4] have done a lot of efforts to analytically show that in sliding phase of system (when s t ð Þ ¼ 0), the error q will converge to zero in a finite time like t ¼ t a .…”

Section: First Main Commentmentioning

confidence: 99%

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