Design of an online tuning modified-grey fuzzy PID controller for nonlinear systems
This paper presents a design of a novel adaptive controller - online tuning modified-Grey fuzzy PID (OTMGFPID) - to deal with nonlinear systems. The OTMGFPID is a combination of a main control unit - online tuning fuzzy PID (OTFPID), and a predictor - online tuning modified-Grey predictor (OTMGP). T...
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| creator | Dinh Quang Truong Kyoung Kwan Ahn Jong Il Yoon Maolin Jin Chin Tae Choi |
| description | This paper presents a design of a novel adaptive controller - online tuning modified-Grey fuzzy PID (OTMGFPID) - to deal with nonlinear systems. The OTMGFPID is a combination of a main control unit - online tuning fuzzy PID (OTFPID), and a predictor - online tuning modified-Grey predictor (OTMGP). The OTFPID controller, which is built from an adaptive proportional-integral-derivative (PID) controller based on an online tuning fuzzy-neural technique and robust checking conditions, is used to drive the system to desired targets. In addition, a smart learning mechanism (SLM) was implemented into the OTFPID in order to optimize smartly its parameters with respect to the control error minimization. The OTMGP with online tuning ability of the predictor step size based fuzzy (FPSS) is used to estimate the actual system output and to create a compensating signal corresponding to the system perturbations. The effectiveness of the proposed OTMGFPID controller has been evaluated by numerical simulations in a comparison with other typical controllers. |
| doi_str_mv | 10.1109/FPM.2011.6045813 |
| format | Conference Proceeding |
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The OTMGFPID is a combination of a main control unit - online tuning fuzzy PID (OTFPID), and a predictor - online tuning modified-Grey predictor (OTMGP). The OTFPID controller, which is built from an adaptive proportional-integral-derivative (PID) controller based on an online tuning fuzzy-neural technique and robust checking conditions, is used to drive the system to desired targets. In addition, a smart learning mechanism (SLM) was implemented into the OTFPID in order to optimize smartly its parameters with respect to the control error minimization. The OTMGP with online tuning ability of the predictor step size based fuzzy (FPSS) is used to estimate the actual system output and to create a compensating signal corresponding to the system perturbations. 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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Control systems fuzzy Gain Mathematical model modified-Grey predictor Noise nonlinear system Nonlinear systems PID controller smart online tuning Tuners |
| title | Design of an online tuning modified-grey fuzzy PID controller for nonlinear systems |
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