Observer-based proportional derivative fuzzy control for singular Takagi-Sugeno fuzzy systems

Ku, Cheung-Chieh; Chang, Wen‐Jer; Tsai, Ming-Hsuan; Lee, Yi‐Chen

doi:10.1016/j.ins.2021.01.023

Cited by 57 publications

(30 citation statements)

References 42 publications

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“…Based on the inequalities (23)(24)(25)(26)(27), then one can rewrite the Lyapunov function (22) as follows:…”

Section:    mentioning

confidence: 99%

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

Chang

2022

IEEE Access

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“…Based on the inequalities (23)(24)(25)(26)(27), then one can rewrite the Lyapunov function (22) as follows:…”

Section:    mentioning

confidence: 99%

“…In the past few decades, the descriptor systems have been efficiently applied to many practical systems, for example, network system, DC motor system, and bio-economic system [20][21][22]. Compared with the standard state-space system, the descriptor system can describe the physical system more accurately and naturally.…”

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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“…However, if only using a traditional state feedback controller to singular systems, the complex model transformations for system matrices are unavoidable. To simplify the derivation process of the stability criteria, the PD feedback scheme was used to discuss control problems in [25][26][27][28][29][30][31][32]. For instance in [25] the stabilization issues for continuous-time and discretetime linear switched singular systems were studied via PD control strategy with the free-weighting matrix technique.…”

Section: Introductionmentioning

confidence: 99%

“…In [26], the passive H ∞ control for the discrete-time linear switched singular systems was studied by using the Schur lemma. The related PD control problems were studied in [27][28][29][30][31][32]. The PD observer issue for discrete-time singular systems was studied in [33].…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Fuzzy Controller Design for Nonlinear Discrete-Time Singular Systems via Proportional Derivative Feedback Scheme

2021

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This paper investigates the observer-based fuzzy controller design method for nonlinear discrete-time singular systems that are represented by Takagi-Sugeno (T-S) fuzzy models. At first, the nonlinearity can be well-approximated with several local linear input-output relationships. The parallel distributed compensation (PDC) technology and the proportional derivative (PD) feedback scheme are then employed to construct the observer-based fuzzy controller. To solve the problem of unmeasured states, the impulsive phenomenon of singular systems, and the PD scheme’s reasonableness, a novel observer-based fuzzy controller is developed. By using the Lyapunov theory and projection lemma, the stability criteria are built in terms of linear matrix inequalities (LMI). Moreover, the gains of fuzzy controller and fuzzy observer can be calculated synchronously by using convex optimization algorithms. Finally, a biological economic system is provided to verify the effectiveness of the proposed fuzzy control method.

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“…Using AIS data, the nonlinear observer has also been applied in designing the exogenous Kalman filter for the visualization and prediction of ship dynamics [26]. Via the T-S fuzzy model, some fruitful fuzzy observer design methods have been developed to estimate and control nonlinear systems such as singular systems [27]. However, the T-S fuzzy model-based observer design method has not been applied to estimating ship dynamics with AIS data.…”

Section: Introductionmentioning

confidence: 99%

Development of Fuzzy Observer Gain Design Algorithm for Ship Path Estimation Based on AIS Data

2021

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This paper develops a Takagi-Sugeno fuzzy observer gain design algorithm to estimate ship motion based on Automatic Identification System (AIS) data. Nowadays, AIS data is widely applied in the maritime field. To solve the problem of safety, it is necessary to accurately estimate the trajectory of ships. Firstly, a nonlinear ship dynamic system is considered to represent the dynamic behaviors of ships. In the literature, nonlinear observer design methods have been studied to estimate the ship path based on AIS data. However, the nonlinear observer design method is challenging to create directly since some dynamic ship systems are more complex. This paper represents nonlinear ship dynamic systems by the Takagi-Sugeno fuzzy model. Based on the Takagi-Sugeno fuzzy model, a fuzzy observer design method is developed to solve the problem of estimating using AIS data. Moreover, the observer gains of the fuzzy observer can be adjusted systemically by a novel algorithm. Via the proposed algorithm, a more suitable or better observer can be obtained to achieve the objectives of estimation. Corresponding to different AIS data, the better results can also be obtained individually. Finally, the simulation results are presented to show the effectiveness and applicability of the proposed fuzzy observer design method. Some comparisons with the previous nonlinear observer design method are also given in the simulations.

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Observer-based proportional derivative fuzzy control for singular Takagi-Sugeno fuzzy systems

Cited by 57 publications

References 42 publications

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

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

Observer-Based Fuzzy Controller Design for Nonlinear Discrete-Time Singular Systems via Proportional Derivative Feedback Scheme

Development of Fuzzy Observer Gain Design Algorithm for Ship Path Estimation Based on AIS Data

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