The paper describes the development of an adaptive fuzzy control strategy for control of dissolved oxygen (DO) concentration on an activated sludge process (ASP). The technique is applied to the Benchmark Simulation Model n.1 (BSM1) which is a standard for performance assessment and evaluation of ASP control strategies. The controller uses DO concentration error feedback and manipulates the flo...

A new kind of multivariable adaptive fuzzy decoupling controller is present for Aero-engine, which consists of multivariable fuzzy decoupling control and fuzzy model reference learning control. A fuzzy inverse model is used to produce and adjust fuzzy rules online. The simulation results show that this controller is effective.

An adaptive fuzzy gain scheduling scheme for robotic arm has been proposed. This paper focus on adaptive fuzzy based tracking and gain controller algorithm for obtaining the joints position relative to the desired trajectory, which drives static and different time variations on the environmental changes. We able to estimate them at any point of time, when t >0 or alternatively, starting from th...

This paper presents the similarity of a class of adaptive fuzzy controllers and a time dependent single rule controller of TakagiSugeno (TS) model. The class of adaptive fuzzy controllers is one of iterative multilayer structure of single input fuzzy controllers (SIFC). On the other hand, in a time dependent single rule controller of TS model, only one rule can be fired at a time. The result mo...

A multi objective Honey Bee Mating Optimization (HBMO) designed by online learning mechanism is proposed in this paper to optimize the double Fuzzy-Lead-Lag (FLL) stabilizer parameters in order to improve low-frequency oscillations in a multi machine power system. The proposed double FLL stabilizer consists of a low pass filter and two fuzzy logic controllers whose parameters can be set by the ...

Intelligent systems may be viewed as a framework for solving the problems of nonlinear system control. The intelligence of the system in the nonlinear or changing environment is used to recognize in which environment the system currently resides and to service it appropriately. This paper presents a general methodology of adaptive control based on multiple models in fuzzy form to deal with plan...

In this paper, we present a combined direct and indirect adaptive control scheme for adjusting an adaptive fuzzy controller, and an adaptive fuzzy identification model parameters. First, using adaptive fuzzy building blocks, with a common set of parameters, we design and study an adaptive controller and an adaptive identification model that have been proposed for a general class of the uncertai...

This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the pro...

Brushless DC (BLDC) motors are commonly used in applications that require high reliability, high efficiency and high power-to-volume ratio such as industrial automations, manufacturing, robotics and aerospace. The speed of a brushless dc motor can be controlled in a closed loop by measuring the actual speed of the motor.PI (Proportional Integral), PID (Proportional Integral Derivative) and fuzz...

This paper presents a novel adaptive fuzzy controller approach of brushless DC motors (BLDCM) without hall sensors. The fuzzy controller adopts fuzzy logic to retune the PID parameters online. Based on the mathematical model of BLDCM introduced, a novel adaptive fuzzy control strategies have been designed in MATLAB/SIMULINK. The results have been recorded under various operating conditions. The...