An Improved Self-Tuning Mechanism of Fuzzy Control by Gradient Descent Method
نویسندگان
چکیده
An improved self-tuning mechanism of fuzzy control by gradient descent method is presented. The membership function parameters are tuned by minimizing some criterion defined on the control output using the steepest gradient descent algorithm. The factor which controls how much the fuzzy controller parameters are altered is adjusted continuously using a set of fuzzy rules. This varying factor is determined with respect to the values of the objective function and its change. An application to the control output optimization of a PI-type fuzzy controller shows the superiority of the proposed selftuning mechanism over a previously published approach in terms of both precision and convergence rate.
منابع مشابه
Tuning a Fuzzy Logic Controller: An introduction
In this paper several tuning methods for Sugeno's fuzzy systems wiu be discussed. &t 4he first case the fuzzy controller is identified off-line based on training data. Following this approach, first the structure of the controller is identified by means of a clustering algorithm. A Kohonen se4f-organizing neural network performs this task. TheE the parameters of the fuzzy controlier (ie. member...
متن کاملTuning a fuzzy logic controller
In this paper several tuning methods for Sugeno's fuzzy systems wiu be discussed. &t 4he first case the fuzzy controller is identified off-line based on training data. Following this approach, first the structure of the controller is identified by means of a clustering algorithm. A Kohonen se4f-organizing neural network performs this task. TheE the parameters of the fuzzy controlier (ie. member...
متن کاملAir-Fuel Ratio Control of a Lean Burn SI Engine Using Fuzzy Self Tuning Method
Reducing the exhaust emissions of an spark ignition engine by means of engine modifications requires consideration of the effects of these modifications on the variations of crankshaft torque and the engine roughness respectively. Only if the roughness does not exceed a certain level the vehicle do not begin to surge. This paper presents a method for controlling the air-fuel ratio for a lean bu...
متن کاملHybrid Algorithm for Fuzzy Model Parameter Estimation based on Genetic Algorithm and Derivative based Methods
Hybrid method for estimation of fuzzy model parameters is presented. The main idea of the method is to apply gradient descent method or Kalman filter as a mutation operator of genetic algorithm for estimation of antecedent parameters of fuzzy “IF-THEN” rules. Thus, part of the individuals in the population mutate by means of gradient descent method or Kalman filter, the others mutate in an ordi...
متن کاملGenetic algorithm-based adaptive fuzzy logic systems for dynamic modeling of quadrotors Unconstrained Evolutionary and Gradient Descent-Based Tuning of Fuzzy-partitions for UAV Dynamic Modeling with Christoffel Symbols of the First Kind
This paper presents a novel fuzzy identification method for dynamic modelling of quadrotor UAVs. The method is based on a special parameterization of the antecedent part of fuzzy systems that results in fuzzy-partitions for antecedents. This antecedent parameter representation method of fuzzy rules ensures upholding of predefined linguistic value ordering and ensures that fuzzy-partitions remai...
متن کامل