This paper presents the application of an adaptive neuro-fuzzy logic on the development of controller for 6 Degree-of-freedom parallel manipulator known as the Stewart platform. This manipulating structure has been well-known for its use as a flight simulator. In this research, the kinematics of the Stewart platform is analyzed first and then neuro-fuzzy logic based controller for controlling l...

Classical control theory is based on the mathematical models that describe the physical plant under consideration. The essence of fuzzy control is to build a model of human expert who is capable of controlling the plant without thinking in terms of mathematical model. The transformation of expert's knowledge in terms of control rules to fuzzy frame work has not been formalized and arbitrary cho...

Distillation is an essential separation process in the chemical and petrochemical industry. The distillation process is a highly nonlinear, complex, interactive and non -stationary, therefore its control is difficult. In the present work an adaptive neuro-fuzzy controller is designed to control a binary distillation process. A conventional PID controller is also designed for comparison purpose....

Article Info Abstract This paper presents a Hybrid Adaptive Neuro Fuzzy Control technique for speed control of BLDC motor drives. The proposed controller is an integration of adaptive neuro fuzzy, fuzzy PID and PD controllers. The objective is to utilize the best attribute of fuzzy PID and PD controllers, which exhibits a better response than the neuro fuzzy controllers. The error back propagat...

The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed sys...

A fuzzy logic controller (FLC) is designed to maintain constant tension for tandem rolling mills. Envisioning fuzzy inference system as neural network and introducing tutor, backward propagation algorithm is used as self-organization technique for FLC to approach the best parameters under supervision. Simulation results exhibit the generalization and adaptivity of neuro-fuzzy controller in offl...

In this paper, an adaptive control method for hybrid position/force control of robot manipulators, based on neuro-fuzzy modelling, is presented. Also, an adaptive neuro-fuzzy compensator compensates the friction force between the endeffector and the surface of the object. Due to the adaptive neuro-fuzzy modelling, the proposed controller is independent of the robot dynamics. Also, the stability...

A neuro-fuzzy controller was designed and implemented using LabVIEW over a mobile robotic platform. The controller is based on fuzzy clusters, neural networks, and search techniques. Also, wireless communication with Bluetooth protocol was used to communicate the robot with the controller running in LabVIEW, allowing a simple collaborative task that consisted in pick and place objects, through ...

A Proportional-Integral (PI) controller and a non-linear Fuzzy and Neuro controller is designed and its application to the regulation of 54V, 2.916kW Quasi-Resonant Buck Converter is comparatively investigated. PI controller involves Proportional gain (Kp) and Integral time (Ki) parameters whose manual tuning provides an appropriate action. Fuzzy logic is on the notion of graded membership and ...

The goal of this work is to compare fuzzy, neural network and neuro-fuzzy approaches to the control of mobile robots. The rst part of this paper is devoted to the formal framework of fuzzy controllers. Results of an example of their use for a mobile robot are discussed. As an experimental platform, the Khepera mobile robot is used. The same example is studied using artiicial neural networks. Fo...