Rule base reduction on a self-learning fuzzy controller
نویسندگان
چکیده
In this paper a methodology to develop a fuzzy rule-based controller is described. The rulebase is obtained by learning from a virtual feedback (PID) controller. The designed controller is supposed to support typical control requirements (i.e. fast-following, zero steady state error, overshoot suppression, etc.) using only a small number of rules. The virtual controller is designed by manual adjusting with one of two alternative methods: simulation of a feedback controlled system using a estimated process model or by means of an on-line training phase.
منابع مشابه
A Practical Review of a Design Method for Fuzzy Controllers Based on Self-learning Algorithm
A method for building the rule-base of a fuzzy controller, using the iterative learning and adaptive neural fuzzy training is tested in practical conditions. This method aims to engage intelligent features to controller design procedure, by implying concepts and techniques from artificial intelligence as learning or adapting. An iterative self-learning algorithm is used to gather useful and tru...
متن کاملA Self-learning Based Fuzzy Controller for Dc Drive Control
A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC) is presented and verified in a practical experiment. The methodology is a simplified version of those presented in available research papers. Some aspects are intentionally ignored as they rarely appear in control system engineering and a SISO process is considered here. The fuzzy inference system obt...
متن کاملSelf-organizing fuzzy control of multi-variable systems using learning vector quantization network
Using learning vector quantization (LVQ) network to construct a self-organizing fuzzy controller (SOFC) for multivariable nonlinear composite systems is developed in this paper. The LVQ network is used to provide information about the better locations of the IF-part membership functions through un-supervised learning. The generated fuzzy rule base is applied to the SOFC and updated by a self-le...
متن کاملImprovement of Rule Generation Methods for Fuzzy Controller
This paper proposes fuzzy modeling using obtained data. Fuzzy system is known as knowledge-based or rule-bases system. The most important part of fuzzy system is rule-base. One of problems of generation of fuzzy rule with training data is inconsistence data. Existence of inconsistence and uncertain states in training data causes high error in modeling. Here, Probability fuzzy system presents to...
متن کاملFuzzy Rule-based Controllers That Learn by Evolving Their Knowledge Base. ?
Fuzzy Logic Controllers may be considered as knowledge-based systems , incorporating human knowledge into their Knowledge Base through Fuzzy Rules and Fuzzy Membership Functions. The deenition of these Fuzzy Rules and Fuzzy Membership Functions is actually aaected by subjective decisions, having a great innuence over the performance of the Fuzzy Controller. In recent years, eeorts have been mad...
متن کامل