In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

Neural network has good nonlinear function approximation ability. It can be widely used to identify the model of controlled plant. In this chapter, the theories of modeling uncertain plant by using two kinds of neural networks: feed-forward neural network and recurrent neural network are introduced. And two adaptive control strategies for robotic tracking control are developed. One is recurrent...

-This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA’s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accura...

This paper investigates the problem of robust output feedback control for a class of uncertain discrete-time fuzzy systems with time delays. The state–space Takagi–Sugeno fuzzy model with time delays and norm-bounded parameter uncertainties is adopted. The purpose is the design of a full-order fuzzy dynamic output feedback controller which ensures the robust asymptotic stability of the closed-l...

This paper investigates the problem of robust output feedback control for a class of uncertain discrete-time fuzzy systems with time delays. The state–space Takagi–Sugeno fuzzy model with time delays and norm-bounded parameter uncertainties is adopted. The purpose is the design of a full-order fuzzy dynamic output feedback controller which ensures the robust asymptotic stability of the closed-l...

In this paper, a multi stage fuzzy Proportional-Integral-Derivative (PID) type controller is proposed to solve the Load Frequency Control (LFC) problem in a restructured power system that operates under deregulation based on the bilateral policy scheme. In each control area, the effects of the possible contracts are treated as a set of new input signal in a modified traditional dynamical model....

This paper presents a comparison between a fuzzy logic controller and a conventional IP controller used for speed control with a direct stator flux orientation control of a doubly fed induction motor. The effectiveness of the proposed control strategy is evaluated under different operating conditions such as of reference speed and for load torque step changes at nominal parameters and in the pr...

Predictive fuzzy PID control theory is developed in this paper, which o€ers a new approach for robust control of time-delay systems. The paper describes the functional structure, design principle, and stability analysis of a new predictive fuzzy PID controller. Sucient computer simulations are provided for illustration and veri®cation. First, the structure of the controller is derived from bot...

This work presents an integrated robust adaptive control scheme that merges the fuzzy control algorithm with the Cerebellar Model Arithmetic Control (CMAC) for unknown systems. The presented adaptation mechanism is used to tune the weight parameters in the CMAC, such that a given ideal stable controller will be best approximated without prior off-line learning phase required. A robust controlle...

The development of a fuzzy-logic controller for a class of industrial hydraulic manipulator is described. The main element of the controller is a PI-type fuzzy control technique which utilizes a simple set of membership functions and rules to meet the basic control requirements of such robots. Using the triangle shaped membership function, the position of the servocylinder was successfully cont...