Extended state observer-based adaptive hierarchical sliding mode control for longitudinal movement of a spherical robot

Yue, Ming; Liu, Baoyin; An, Cong; Sun, Xiaoxiao

doi:10.1007/s11071-014-1511-1

Cited by 34 publications

(34 citation statements)

References 19 publications

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“…1, and the dynamics of system are given as (33), where M 11 = m 1 R 2 + m 1 l 2 1 − m 1 l 2 1 cos(q 2 ) + I 1 ; M 12 = M 21 = −m 1 Rl 1 cos(q 2 ); M 22 = m 1 l 2 1 + I 2 ; C 11 = m g k t k m k 2 g ∕R m + Beq + 2m 1 l 2 1q 2 sin(q 2 )cos(q 2 ); C 12 = m 1 l 1 Ṙq 2 sin(q 2 ); C 21 = −m 1 l 2 1 sin(q 2 )cos(q 2 ); C 22 = Beq; G 1 = 0; G 2 = −m 1 l 2 gsin(q 2 ); h H = m g k t k g ∕R m . 1, and the dynamics of system are given as (33), where M 11 = m 1 R 2 + m 1 l 2 1 − m 1 l 2 1 cos(q 2 ) + I 1 ; M 12 = M 21 = −m 1 Rl 1 cos(q 2 ); M 22 = m 1 l 2 1 + I 2 ; C 11 = m g k t k m k 2 g ∕R m + Beq + 2m 1 l 2 1q 2 sin(q 2 )cos(q 2 ); C 12 = m 1 l 1 Ṙq 2 sin(q 2 ); C 21 = −m 1 l 2 1 sin(q 2 )cos(q 2 ); C 22 = Beq; G 1 = 0; G 2 = −m 1 l 2 gsin(q 2 ); h H = m g k t k g ∕R m .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Consider the Rotating Inverted Pendulum system as shown in Fig. 1, and the dynamics of system are given as (33)…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In order to avoid the peak phenomenon which is arisen by the difference between the system initial states and the observer initial states, is selected as [33]:…”

Section: Tsm-based Observermentioning

confidence: 99%

“…One of the ways to deal with the issue is that an effective observer is available to estimate and compensate it to the controller. An important marker of ESO is the convergent performance, it ensures that the observer can estimate the states and the extended state exactly [33]. An important marker of ESO is the convergent performance, it ensures that the observer can estimate the states and the extended state exactly [33].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

FTESO‐Based Finite Time Control for Underactuated System Within a Bounded Input

Wang¹,

Zhou²,

Chen³

et al. 2017

Asian Journal of Control

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Finite time control problem is investigated for a class of underactuated systems with uncertainties and external disturbances. For the sake of expanding control region furthest within a bound input, finite time extended state observer (FTESO) and a novel adaptive terminal sliding mode (ATSM) controller are applied to improve the stability performance of system. Compared to the general extended state observer (ESO), FTESO makes use of fractional powers to reduce the estimation errors to zero in finite time. The coordinate transformation is made for more degrees of design freedom. Rigorous analysis of finite time convergence results has been performed through Lyapunov theory and sufficient conditions are provided for the observer/controller-design. Finally, simulation results on the Rotating Inverted Pendulum are given to demonstrate the effectiveness of the proposed controller and observer.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

“…Consider the Rotating Inverted Pendulum system as shown in Fig. 1, and the dynamics of system are given as (33)…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In order to avoid the peak phenomenon which is arisen by the difference between the system initial states and the observer initial states, is selected as [33]:…”

Section: Tsm-based Observermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

FTESO‐Based Finite Time Control for Underactuated System Within a Bounded Input

Wang¹,

Zhou²,

Chen³

et al. 2017

Asian Journal of Control

View full text Add to dashboard Cite

show abstract

“…Therefore, ESO has been applied to various engineering practices, such as flight control, chemical process control, guidance law design, robot control, and motion control etc. [13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A novel extended state observer

et al. 2015

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Hybrid super‐twisting fractional‐order terminal sliding mode control for rolling spherical robot

Parizi

Salemizadehparizi

Vanaei

et al. 2021

Asian Journal of Control

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The unmodeled parameters, uncertainties, chattering, and disturbances can be serious problems for a controller. These issues decrease the performance of the controller and make it difficult to have a satisfactory movement path as well. This paper presents a novel hybrid super‐twisting fractional‐order terminal sliding mode controller (HSTFOTSMC) for a rolling spherical robot (RSR) considering bounded model uncertainties for robot dynamics in presence of external disturbances and noise. The controller is based on a new adaptive fractional‐order terminal sliding surface. The stability of the proposed controller is proved by the Lyapunov theory, and then, it is tuned by a novel extended grey wolf optimizing (EGWO) algorithm to adjust the controller parameters, and assure to achieve the precise robot performance. The results of the optimized controller (EGWO‐HSTFOTSMC) are compared with the typical sliding mode controller (SMC), fractional‐order terminal sliding mode controller (FOTSMC), and super‐twisting fractional‐order terminal sliding mode controller (STFOTSMC), which demonstrate the effectiveness of the controller scheme. The controller implementation can potently eliminate the impacts of disturbances, noise, and uncertainties; meanwhile, it decreases the tracking error and increases the convergence speed of robot responses.

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Extended state observer-based adaptive hierarchical sliding mode control for longitudinal movement of a spherical robot

Cited by 34 publications

References 19 publications

FTESO‐Based Finite Time Control for Underactuated System Within a Bounded Input

FTESO‐Based Finite Time Control for Underactuated System Within a Bounded Input

A novel extended state observer

Hybrid super‐twisting fractional‐order terminal sliding mode control for rolling spherical robot

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