Robust Fuzzy Control with Transient and Steady-State Performance Constraints for Ship Fin Stabilizing Systems

Chang, Chih-Ming; Chang, Wen‐Jer

doi:10.1007/s40815-018-0555-7

Cited by 21 publications

(12 citation statements)

References 37 publications

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“…The fuzzy rules of the proposed method are less than the method in [32] because the proposed method is based on the polynomial description. Namely, the proposed method provides better performance with less fuzzy rules than the method in [32]. As Figures 9 and 10 show, although system (49)-( 52) is affected by external disturbance, the responses driven by two controllers are kept around the zero.…”

Section: B Ship Fin Stabilizing Systemmentioning

confidence: 97%

“…( ) To show the applicability, the method in [32] is introduced to compare with the proposed method. Since the upper and lower bound of time-varying parameter are opposite signs, only Theorem 1 can be applied to system ( 49 , in which ( )…”

Section: B Ship Fin Stabilizing Systemmentioning

confidence: 99%

“…2 − 0.005198x 2 − 30300. Besides, the control gains in [32] are utilized to build a controller in the comparison. After designing the PDPF controller u, the responses in (49)-(52) are, respectively, sated in Figures 9 and 10 with the same initial condition as x(0) = π/18 0 T .…”

Section: B Ship Fin Stabilizing Systemmentioning

confidence: 99%

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Passive Fuzzy Controller Design for the Parameter-Dependent Polynomial Fuzzy Model

Sun

Jian

et al. 2023

Mathematics

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This paper discusses a passive control issue for Nonlinear Time-Varying (NTV) systems subject to stability and attenuation performance. Based on the modeling approaches of Takagi-Sugeno (T-S) fuzzy model and Linear Parameter-Varying (LPV) model, a Parameter-Dependent Polynomial Fuzzy (PDPF) model is constructed to represent NTV systems. According to the Parallel Distributed Compensation (PDC) concept, a parameter-dependent polynomial fuzzy controller is built to achieve robust stability and passivity of the PDPF model. Furthermore, the passive theory is applied to achieve performance, constraining the disturbance effect on the PDPF systems. To develop the stability criteria, by introducing a parameter-dependent polynomial Lyapunov function, one can derive some stability conditions, which belong to the term of Sum-Of-Squares (SOS) form. Based on the Lyapunov function, two stability criteria are proposed to design the corresponding PDPF controller, such that the NTV system is robustly stable and passive. Finally, two examples are applied to demonstrate the effectiveness of the proposed stability criterion.

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Section: B Ship Fin Stabilizing Systemmentioning

confidence: 97%

Section: B Ship Fin Stabilizing Systemmentioning

confidence: 99%

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Passive Fuzzy Controller Design for the Parameter-Dependent Polynomial Fuzzy Model

Sun

Jian

et al. 2023

Mathematics

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“…Another importance of the TSFM is that can use many recognized linear control theories to analyze the stability conditions of nonlinear systems [13]. Consequently, many stability analyses and controller syntheses of practical systems have been made through the TSFM, such as unmanned marine vehicles, ship fin stabilizing systems, maglev vehicle suspension systems [14][15][16]. On the other hand, the TSFM has been applied to LS systems.…”

Section: Introductionmentioning

confidence: 99%

Passive Decentralized Fuzzy Control for Takagi-Sugeno Fuzzy Model Based Large-Scale Descriptor Systems

Chang

2022

IEEE Access

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“…The T‐S fuzzy model control method has also been widely applied in many practical industrial systems recently. Significant efforts have been devoted to study the analysis and synthesis problems of T‐S fuzzy control systems [4–7].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy controller design for nonlinear singular systems with external noises subject to passivity constraints

Chang

Varadarajan

2020

Asian Journal of Control

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This paper applies the state derivative feedback method and proportional plus derivative state feedback method to design the fuzzy controllers for the nonlinear singular systems with external noises. The Takagi‐Sugeno fuzzy modeling technology is employed in this paper to represent the nonlinear singular systems with external noise. Considering the singular Takagi‐Sugeno fuzzy model, the passivity constraint is chosen to treat the external noises for the controlled systems. By using the parallel distributed compensation method, the fuzzy controller is designed to satisfy the Lyapunov stability conditions and passivity constraints simultaneously. These sufficient conditions can be effectively solved in terms of linear matrix inequalities, which can be solved via the convex optimization technique. At last, some numerical examples are provided to verify the applicability and effectivity of the proposed fuzzy controller design methods.

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Robust Fuzzy Control with Transient and Steady-State Performance Constraints for Ship Fin Stabilizing Systems

Cited by 21 publications

References 37 publications

Passive Fuzzy Controller Design for the Parameter-Dependent Polynomial Fuzzy Model

Passive Fuzzy Controller Design for the Parameter-Dependent Polynomial Fuzzy Model

Passive Decentralized Fuzzy Control for Takagi-Sugeno Fuzzy Model Based Large-Scale Descriptor Systems

Fuzzy controller design for nonlinear singular systems with external noises subject to passivity constraints

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