Nonfragile Retarded Sampled-Data Switched Control of T–S Fuzzy Systems and Its Applications

Subramanian, K.; Joo, Young Hoon

doi:10.1109/tfuzz.2019.2940432

Cited by 32 publications

(12 citation statements)

References 34 publications

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“…For example, the stability problem has been studied for T-S fuzzy systems via membership function dependent LKF in [33]. Furthermore, when compared with usual control method [13], switched control approach for T-S fuzzy systems diminish the number of LMIs and attain maximum sampling interval, which has been studied in [33,34]. Although a lot of attempts had made on the investigation of T-S fuzzy systems stability, when the memory-based coupling switched SDC information is taken into account, the stability of fuzzy systems has been drawn very little research, which motivates us to carry on the current research.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy membership function-dependent switched control for nonlinear systems with memory sampled-data information

Visakamoorthi

Subramanian²,

Muthukumar³

2022

Soft Comput

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In this paper, a fuzzy memory-based coupling sampled-data control (SDC) is designed for nonlinear systems through the switched approach. Compared with the usual SDC scheme, by employing the Bernoulli sequence, a more general coupling switched SDC that involving the signal transmission delay is designed. The Lyapunov-Krasovskii Functional (LKF) is presented with the available characteristics of the membership function, and a coupling sampling pattern, for the T-S fuzzy systems.Based on LKF, together with time derivative information of membership function, and the generalized N -order free-matrix-based inequality, the suitable conditions are obtained in terms of linear matrix inequalities (LMIs) for guaranteeing the asymptotic stability and stabilization of the concerned system. Then the desired fuzzy coupling SDC gain is attained from the solvable LMIs. In the end, two examples are given to validate the derived theoretical results.

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Section: Introductionmentioning

confidence: 99%

Fuzzy membership function-dependent switched control for nonlinear systems with memory sampled-data information

Visakamoorthi

Subramanian²,

Muthukumar³

2022

Soft Comput

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“…The basic control of sliding variable structure model can be designed and realized through the transformation and derivation of UVMS dynamic model. The switching gain of the sliding mode is adjusted through fuzzy control logic [22,17,12], and the fluid interference and the coupling of body manipulator are realized [7,28]. The effect and other additional mass disturbance are processed by fuzzy function to eliminate the influence on the pose and trajectory control of the manipulator [1].…”

mentioning

confidence: 99%

Finite-time sliding mode control for UVMS via T-S fuzzy approach

Xiang¹,

Ren²,

He³

et al. 2022

DCDS-S

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<p style='text-indent:20px;'>In order to solve the control problem of Underwater Vehicle with Manipulator System (UVMS), this paper proposes a finite-time sliding mode control strategy via T-S fuzzy approach. From the general dynamic model of UVMS and considering the influence between the manipulator and the underwater vehicle, hydrodynamic damping, buoyancy and gravity as the fuzzy items, we establish global fuzzy dynamic model and design a closed-loop fuzzy sliding mode controller. We prove the model in theory from two aspects: the reachability of sliding domain and the finite-time boundedness. We also give the solution of the controller gain. A simulation on the actual four joint dynamic model of UVMS with two fuzzy subsystems is carried out to verify the effectiveness of this method.</p>

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“…Interestingly, the main feature of the T-S fuzzy system is that any smooth nonlinear dynamics can be approximated as a collection of local linear dynamics with their corresponding membership functions. The easy structure of the T-S fuzzy model offers to apply the linear control theories on it [1,6,22,23,25]. Recently, most of the existing research works on fuzzy systems mainly focus on the reduction of conservatism by employing some advanced mathematical techniques, such as non-parallel distributed compensation law [2], fuzzy membership dependent Lyapunov functional approach [8], and augmented Lyapunov-Krasovskii functional approach [12].…”

mentioning

confidence: 99%

“…ẋT (s)ϑ 2 P ẋ(s)dsdθ, Now, by calculating the time derivative of (11) along the solutions of the considered system (6), it follows that…”

mentioning

confidence: 99%

“…Rule 1: Further, the membership functions and disturbances are chosen as Further, the state responses curve of T-S fuzzy system (6) with and without controller are plotted in FIGURES 5 and 6, respectively . From FIGURE 5, it can be seen that the state curve converges to zero in a short period, which shows that the T-S fuzzy system ( 6) is asymptotically stable under the proposed control design (5).…”

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confidence: 99%

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Robust $ H_\infty $ resilient event-triggered control design for T-S fuzzy systems

Sakthivel

Selvaraj

Kim

et al. 2022

DCDS-S

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<p style='text-indent:20px;'>This paper investigates the resilient <inline-formula><tex-math id="M2">\begin{document}$ H_\infty $\end{document}</tex-math></inline-formula> event-triggered control problem for Takagi-Sugeno fuzzy system with time-varying delay and external disturbance. Contrary to some existing results, the considered event-triggered conditions are verified only at each sampling instant because it is difficult to prove Zeno-freeness for a continuous event-triggered mechanism in the presence of external disturbance. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, sufficient conditions are derived in the form of linear matrix inequalities to ensure the asymptotic stability and the <inline-formula><tex-math id="M3">\begin{document}$ H_\infty $\end{document}</tex-math></inline-formula> performances of closed-loop systems. More precisely, the proposed control design not only improve robust performance but also save the communication resources. Finally, the obtained theoretical results are verified through numerical simulation, which demonstrate the efficiency and advantages of the proposed method.</p>

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Nonfragile Retarded Sampled-Data Switched Control of T–S Fuzzy Systems and Its Applications

Cited by 32 publications

References 34 publications

Fuzzy membership function-dependent switched control for nonlinear systems with memory sampled-data information

Fuzzy membership function-dependent switched control for nonlinear systems with memory sampled-data information

Finite-time sliding mode control for UVMS via T-S fuzzy approach

Robust $ H_\infty $ resilient event-triggered control design for T-S fuzzy systems

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