Adaptive fuzzy identification and predictive control for industrial processes
نویسندگان
چکیده
منابع مشابه
Adaptive fuzzy identification and predictive control for industrial processes
This paper proposes a method for adaptive identification and control for industrial applications. The learning of a T-S fuzzy model is performed from input/output data to approximate unknown nonlinear processes by a hierarchical genetic algorithm (HGA). The HGA approach is composed by five hierarchical levels where the following parameters of the T-S fuzzy system are learned: input variables an...
متن کاملControlling Nonlinear Processes, using Laguerre Functions Based Adaptive Model Predictive Control (AMPC) Algorithm
Laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. Therefore, it is widely adopted for complex industrial process control. In this work, Laguerre function based adaptive model predictive control algorithm (AMPC) was implemented to control continuous stirred tank rea...
متن کاملUsing Fuzzy Grey Cognitive Maps for Industrial Processes Control
Recently, Fuzzy Grey Cognitive Maps (FGCM) has been proposed as a Grey System theory-based FCM extension. Grey systems have become a very effective theory for solving problems within environments with high uncertainty, under discrete small and incomplete data sets. The benefits of FGCMs over conventional FCMs make evident the significance of developing a greyness-based cognitive model such as F...
متن کاملA neuro-fuzzy supervisory control system for industrial batch processes
The automation of complex industrial batch processes is a difficult problem due to the extremely nonlinear and variable system behavior or the conflicting goals within the different process phases. The introduction of a single multipleinput multiple-output controller (e.g. fuzzy logic (FL) controller) is not useful because of the rather high design effort and the low transparency of its complex...
متن کاملAn Efficient Adaptive Fuzzy Control Scheme for Industrial Manipulators
This paper develops a generalized adaptive fuzzy control scheme for MIMO nonlinear second order systems. Here, the example robotic manipulators is used to illustrate the control algorithm. The controller for each degree of freedom (DOF) consists of a feedback fuzzy PD systems used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feed...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2013
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2013.06.057