Fuzzy Controllers With Maximum Sensitivity for Servosystems

Precup, Radu‐Emil; Preitl, Ștefan; Korondi, Péter

doi:10.1109/tie.2007.893053

Cited by 76 publications

(25 citation statements)

References 24 publications

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“…The stability analysis of T-S fuzzy PID control systems is investigated based on the small gain theorem [17], the passivity theory [18], the describing function method [19], and the circle criterion [20,21], respectively. The T-S fuzzy PID controllers are applied to human arterial pressure control [16] and motor control [22]. It is worth noting that the controlled plants in [16,[18][19][20][21][22] are linear systems rather than nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

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fuzzy PID control synthesis for Takagi–Sugeno fuzzy systems

Cao

Gao

Lam

et al. 2016

IET Control Theory & Applications

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This paper proposes a kind of H ∞ fuzzy PID control synthesis method for Takagi-Sugeno (T-S) fuzzy systems. The basic idea of the presented method is to transform the fuzzy PID controller design problem into that of the fuzzy static output feedback (SOF) controller design. Based on an iterative linear matrix inequality (ILMI) algorithm, the fuzzy SOF control laws can be obtained. After that, the fuzzy PID controller is recovered from the fuzzy SOF controller. Simulation examples are given to show the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

“…The T-S fuzzy PID controllers are applied to human arterial pressure control [16] and motor control [22]. It is worth noting that the controlled plants in [16,[18][19][20][21][22] are linear systems rather than nonlinear systems. In [23], a neural networkbased learning method is used for tuning the parameters of the fuzzy PID controllers.…”

Section: Introductionmentioning

confidence: 99%

fuzzy PID control synthesis for Takagi–Sugeno fuzzy systems

Cao

Gao

Lam

et al. 2016

IET Control Theory & Applications

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“…In [14], the describing function method is used to analyze the stability of the fuzzy PI and PD control systems. Both the Mamdani and T-S fuzzy PID controllers are deployed in the permanent magnet synchronous motor drive control systems in order to improve the transient response and enhance the disturbance rejection ability [15][16][17][18]. Although significant efforts have been devoted to the design of the fuzzy PID, PI, and PD controllers, there are still not enough rigorous theoretical methods for the fuzzy controller design, i.e., how to design fuzzy PID, PI, and PD controllers for nonlinear plants with assured stability.…”

Section: Introduction (Heading 1)mentioning

confidence: 99%

Stability analysis of T-S fuzzy PD, PI, and PID control systems

Cao

Gao

Wang³

et al. 2015

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

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Abstract-In this paper, simple and systematic ways of designing stabilization fuzzy PID (Proportional-Integral-Differential), PI (Proportional-Integral), and PD (Proportional-Differential) controllers for the Takagi-Sugeno fuzzy model are proposed. The state space representations of the fuzzy PID, PI, and PD controllers are firstly presented. Then we equivalently transform the fuzzy PID (PI, or PD) control system into the fuzzy static output feedback control system. The fuzzy static output feedback controller design for the latter system can be efficiently solved via the existing numerical optimization methods with some conservatism. Consequently, the fuzzy PID (PI, or PD) controller can be derived due to the one-to-one correspondence between the fuzzy PID controller and the fuzzy static output feedback controller. A simulation example is also given to demonstrate the effectiveness of our proposed methods.

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“…Our approach is advantageous because it is relatively simple and it can be incorporated in many fuzzy control structures [12], [13], [14], [15], [16], [17], [18], [19]. Three fuzzy models are offered and compared using simulation results.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Fuzzy Modeling of Electromagnetic Actuated Clutch Systems

Claudia-Adina

Precup

Marius

et al. 2013

INT J COMPUT COMMUN

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This paper proposes an approach to fuzzy modeling of a nonlinear servo system application represented by an electromagnetic actuated clutch system. The nonlinear model of the process is simplified and linearized around several operating points of the input-output static map of the process. Discrete-time Takagi-Sugeno (T-S) fuzzy models of the processes are derived on the basis of the modal equivalence principle; the rule consequents of these T-S fuzzy models contain the state-space models of the process. Three discrete-time T-S fuzzy models are suggested, compared and validated by simulation results.

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Fuzzy Controllers With Maximum Sensitivity for Servosystems

Cited by 76 publications

References 24 publications

fuzzy PID control synthesis for Takagi–Sugeno fuzzy systems

fuzzy PID control synthesis for Takagi–Sugeno fuzzy systems

Stability analysis of T-S fuzzy PD, PI, and PID control systems

An Approach to Fuzzy Modeling of Electromagnetic Actuated Clutch Systems

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