A Model-Free Neuro-Fuzzy Predictive Controller for Compensation of Nonlinear Plant Inertia and Time Delay
نویسندگان
چکیده
The aim is to develop simple for industrial use neuro-fuzzy (NF) predictive controllers (NFPCs) that improve the system performance and stability compensating the nonlinear plant inertia and time delay. A NF plant predictor is trained from real time plant control data and validated to supply a main model-free fuzzy logic controller with predicted plant information. A proper prediction horizon is determined via simulation investigations. The NFPC closed loop system stability is validated based on a parallel distributed compensation (PDC) approximation of the NFPC. The PDC can easily be embedded in industrial controllers. The proposed approach is applied for the real time air temperature control in a laboratory dryer. The improvements are reduced overshoot and settling time.
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ورودعنوان ژورنال:
- Informatica, Lith. Acad. Sci.
دوره 28 شماره
صفحات -
تاریخ انتشار 2017