A sliding mode observer for uncertain nonlinear systems based on multiple models approach

Hfaïedh, Kaïs; Dahech, Karim; Damak, Tarak

doi:10.1007/s11633-016-0970-x

Cited by 14 publications

(2 citation statements)

References 8 publications

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“…In [22], a SMO was developed for stochastic nonlinear descriptor systems, and they also designed a sliding mode controller for the SMO. In [11] and [23], SMOs were designed for T-S fuzzy descriptors systems. In [19,28,29,31], SMOs were designed to estimate the faults, and then fault tolerant controllers were designed by using the estimated fault information.…”

Section: Introduction T-s Fuzzy Modelmentioning

confidence: 99%

Sliding mode observer based control for T-S fuzzy descriptor systems

Wang¹

2022

MFC

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<p style='text-indent:20px;'>In this paper, the problem of sliding mode observer (SMO) based sliding mode control (SMC) for nonlinear descriptor delay systems is studied. First, based on the T-S fuzzy dynamic modeling technique, the nonlinear descriptor system is transformed into a combination of local linear models. Then, a integral-type sliding surface (ITSS) based SMO is constructed for the error system. In the sequel, sufficient linear matrix inequality (LMI) conditions are established to ensure the admissibility of the sliding motions and obtain the observer gain matrix. Furthermore, two novel SMC laws are developed to ensure the reachability conditions and stabilize the descriptor systems. Finally, simulations are provided to show the effectiveness of the method.</p>

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Section: Introduction T-s Fuzzy Modelmentioning

confidence: 99%

Sliding mode observer based control for T-S fuzzy descriptor systems

Wang¹

2022

MFC

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“…The number of layers and coefficients of this observer need to be adjusted accordingly, and the input of the observer at each layer linearly accumulates the output of the observer at the previous layer. In [11], a novel sliding mode observer-based on multiple modes approach is designed for the state estimation of a non-linear system with time-varying uncertainties. Similar to ESO, the traditional sliding mode observer and disturbance observer are also highly sensitive to measurement noise.…”

Section: Introductionmentioning

confidence: 99%

Tele‐aiming control design for reconnaissance robot using a strong tracking multi‐model extended super‐twisting observer

Feng²,

Zhang

et al. 2022

IET Control Theory & Appl

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In this study, a tele‐aiming control system for reconnaissance robots is proposed, capable of enabling operators to quickly control the robot to aim at and track the manoeuvring target with random motion characteristics under measurement noise. To track such manoeuvring targets, a cascaded multi‐model super‐twisting observer is designed. First, the system uncertainty and the inertial impact force disturbance generated during rapid tele‐aiming are expanded into a lumped disturbance state. Subsequently, a strong tracking filter is employed to filter and estimate the system output and the lumped disturbance, and the output of the filter is input into the multi‐model extended state super‐twisting observer. The final second‐order state estimation and lumped disturbance estimation of the augmented system are conducted in accordance with the weighted sum of all super‐twisting observers. Lastly, a non‐singular terminal sliding mode controller is designed to compensate for the lumped disturbance and achieve the fast trajectory tracking. To verify the effectiveness of the proposed observer‐based controller, a series of manoeuvring target tracking experiments was performed. As revealed by the experimental results, the proposed controller can quickly control the reconnaissance robot to aim at and track the manoeuvring target with random abrupt motion characteristics under measurement noise disturbance.

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