Control of dynamical processes using an on-line rule-adaptive fuzzy control system

He, Shiyi; Tan, Shaohua; Hang, Chang-Chieh; Wang, Peizhuang

doi:10.1016/0165-0114(93)90356-m

Cited by 61 publications

(11 citation statements)

References 6 publications

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“…For conventional controllers, those requirements tend to undo each other. The dotted curve, which is the response of the discontinuous method of [11], vibrates acutely. Note that the same rising procedures of the solid and the dotted curves results from the same parameters and fuzzy table.…”

Section: Simulation Experimentsmentioning

confidence: 98%

Self-optimizing fuzzy controller for nonlinear system with constraints

2011

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

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This paper presents a self-optimizing fuzzy controller for nonlinear dynamic plants whose model (including nonmathematical models and expert knowledge) is unknown. A new fuzzy algorithm is presented to improve control performances. Furthermore, a global meta-heuristic algorithm is presented to optimize the fuzzy parameters and to satisfy some nonlinear constraints. The numerical simulated experiments show the good performance on a time-varying parameters nonlinear plant.

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Section: Simulation Experimentsmentioning

confidence: 98%

Self-optimizing fuzzy controller for nonlinear system with constraints

2011

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

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“…However, a general systematic theory for stability analysis and control design of conventional fuzzy control systems is still out of reach. Additional references on the topic of conventional fuzzy control can be found in [5], [62], [66], [88], [99], [108], [158], [160]- [162], [164], [165], [173], [176], [233], [247], [278], [325], and [343].…”

Section: A Conventional Fuzzy Control (Mamdani Type Fuzzy Control)mentioning

confidence: 99%

A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

Feng

2006

IEEE Trans. Fuzzy Syst.

1,504

629

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“…Combining the tradition PID with the advanced control tactics is available for solving the above-mentioned problem [2] . Some new control arithmetic as fuzzy control, NN control and self-adaptive control have appeared in recent years.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-PID controlled lift feedback fin stabilizer

Liang

Huang

Liang

2008

J. Marine. Sci. Appl.

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Conventional PID controllers are widely used in fin stabilizer control systems, but they have time-variations, nonlinearity, and uncertainty influencing their control effects. A lift feedback fuzzy-PID control method was developed to better deal with these problems, and this lift feedback fin stabilizer system was simulated under different sea condition. Test results showed the system has better anti-rolling performance than traditional fin-angle PID control systems.

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Control of dynamical processes using an on-line rule-adaptive fuzzy control system

Cited by 61 publications

References 6 publications

Self-optimizing fuzzy controller for nonlinear system with constraints

Self-optimizing fuzzy controller for nonlinear system with constraints

A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

Fuzzy-PID controlled lift feedback fin stabilizer

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