Optimal parallel-distributed-compensation controller design for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay systems by using the orthogonal function approach–assisted genetic algorithm

Chou, Fu-I; Hsu, Ming-Ren; Ho, Wen-Hsien

doi:10.1177/1077546320936901

Cited by 4 publications

(5 citation statements)

References 28 publications

(37 reference statements)

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“…Then, the PDC method is applied to design the fuzzy controller for the IT2 T-S fuzzy model (12). Via the PDC method, the fuzzy controller corresponding to each subsystem is designed, and the overall fuzzy controller is obtained through the "blending" process.…”

Section: System Descriptions and Problem Statementsmentioning

confidence: 99%

“…Substituting ( 14) into ( 12), the fuzzy controller ( 14) is applied to control the IT2 T-S fuzzy system (12) with saturated control input ∼ u(t) as follows:…”

Section: System Descriptions and Problem Statementsmentioning

confidence: 99%

“…The T-S fuzzy model can also be used to solve the actuator saturation problem for nonlinear systems [7][8][9]. In order to develop the fuzzy controller design method, a so-called "Parallel Distributed Compensation" (PDC) method was proposed for the T-S fuzzy model [10][11][12][13]. However, the state of practical engineer systems or controllers may differ from the original due to service life and frequency.…”

Section: Introductionmentioning

confidence: 99%

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Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Chang

Lin

et al. 2021

Processes

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In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

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Section: System Descriptions and Problem Statementsmentioning

confidence: 99%

“…Substituting ( 14) into ( 12), the fuzzy controller ( 14) is applied to control the IT2 T-S fuzzy system (12) with saturated control input ∼ u(t) as follows:…”

Section: System Descriptions and Problem Statementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Chang

Lin

et al. 2021

Processes

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“…1 In the Takagi-Sugeno fuzzy model, each fuzzy rule for the local linear control system is represented by a linear dynamic equation. [2][3][4][5][6][7] The overall nonlinear control system is then formalized by combining the fuzzy rules. Therefore, linear control theory is generally used in controller design.…”

Section: Introductionmentioning

confidence: 99%

Stable and quadratic-optimal parallel-distributed-compensation controller design for time-varying Takagi–Sugeno fuzzy model System: A complementary computational approach

Chou

2022

Measurement and Control

Self Cite

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A complementary computational approach is proposed for the time-varying Takagi–Sugeno fuzzy model system (TVTSFMS). The proposed approach integrates orthogonal-functional approach (OFA), hybrid Taguchi genetic algorithm (HTGA), and a stabilizability condition (SC) for use in designing stable and quadratic-optimal parallel-distributed-compensation (SQOPDC) controllers for optimal control problems. First, the SC was set according to linear matrix inequalities (LMIs). Next, OFA was used to derive an algorithm that only required algebraic computation to solve the TVTSFMS. Finally, The HTGA could be used to search the SQOPDC controller for the TVTSFMS. The SQOPDC controller obtained by the proposed complementary computational approach was evaluated in a case study of a vibratory pendulum design; the successful design verified the usability of the proposed hybrid intelligent computing method.

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“…In Reference 19, a new fast adaptive unknown input observer is proposed for linear systems with unknown perturbations to improve their fault estimation performance. In the framework of T‐S fuzzy model, the finite element of the T‐S fuzzy system was extensively studied in References 20‐23. However, only linear systems or ordinary fuzzy systems are mainly researched, and singular perturbed fuzzy nonlinear systems are not considered.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective optimization‐based robust fault estimation observer design for fuzzy singularly perturbed systems with time‐varying state delays

Zeng

Sun

Huang

et al. 2022

Optim Control Appl Methods

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In this paper, the problem of multi-objective robust fault estimation based on observer is addressed for T-S fuzzy nonlinear singularly perturbed systems with time-varying state delay and external disturbance. Under H ∞ performance constraint, a fuzzy augmented fault estimation observer is introduced to improve the performance of actuator and sensor fault estimation simultaneously. The sufficient conditions for the existence of fault estimator are given in the form of LMIs, where 𝜀-dependent Lyapunov function is considered. The given multi-objective fault estimator design strategy has a good ability to suppress external disturbance and ensure the estimation accuracy and convergence rate work well for all 𝜀 ∈ (0, 𝜀]. Then the largest stability bound and the best attenuation capacity are guaranteed by deriving a modified optimal algorithm. Finally, two examples are given to illustrate the feasibility and correctness of the proposed design method.

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Optimal parallel-distributed-compensation controller design for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay systems by using the orthogonal function approach–assisted genetic algorithm

Cited by 4 publications

References 28 publications

Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Stable and quadratic-optimal parallel-distributed-compensation controller design for time-varying Takagi–Sugeno fuzzy model System: A complementary computational approach

Multi‐objective optimization‐based robust fault estimation observer design for fuzzy singularly perturbed systems with time‐varying state delays

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