Navigation of multiple mobile robots using neuro-fuzzy controller has been discussed in this paper. In neuro-fuzzy controller the output from the neural network is fed as an input to fuzzy controller and the final outputs from the fuzzy controller are used for motion control of robots. The inputs to the neural network are obtained from the robot sensors (such as left, front, right obstacle dist...

By combining the fuzzy theory and neural network technology, a fuzzy neural network (FNN) is proposed in this paper, whose learning algorithms are developed by steep algorithm. The excitation system model based on FNN is also derived in this paper, which can be used for on-line and off-line analysis and control respectively. The simulation results demonstrate that the FNN models can give precis...

introduction according to the shortage of water resources in the world, it seems necessary the use of refined water, particularly in arid and semi-arid areas such as iran. the correct treatment, management and the control of refining process needs to investigate effective parameters in this process precisely. therefore, because of the uncertainty and complexity in refining qualitative parameter...

Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM to improve the fault such as poor convergence and ...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on T-S fuzzy model. Through T-S fuzzy recursive neural network predictor ...

To improve the problem that the parameter identification for fuzzy neural network has many time complexities in calculating, an improved T-S fuzzy inference method and an parameter identification method for fuzzy neural network are proposed. It mainly includes three parts. First, improved fuzzy inference method based on production term for T-S Fuzzy model is explained. Then, compared with exist...

This paper proposes a Fuzzy Logic and Neural Network control system that is able to guide the Mobile robots (AmigoBot and P3DX) traverse through a maze with arbitrary obstacles and computed data and algorithm in Personal Computer (PC) in wireless system. For input data, controller (Fuzzy Logic and Neural Network) receives data from sensors (sonar and laser range finder). This paper checked the ...

To address deficiencies in the process of fault diagnosis of belt conveyor, this study uses a BP neural network algorithm combined with fuzzy theory to provide an intelligent fault diagnosis method for belt conveyor and to establish a BP neural network fault diagnosis model with a predictive function. Matlab is used to simulate the fuzzy BP neural network fault diagnosis of the belt conveyor. R...