A nonparametric approach using artificial intelligence in vibration and noise reduction of flexible systems

2013 ◽  
Vol 228 (8) ◽  
pp. 1329-1347 ◽  
Author(s):  
Ali Zolfagharian ◽  
Amin Noshadi ◽  
Seyed Ebrahim Ghasemi ◽  
Mohd Zarhamdy Md Zain
Keyword(s):  
Artificial Intelligence ◽  
High Speed ◽  
Fuzzy Controller ◽  
Nonlinear System Identification ◽  
Control Area ◽  
Real Time Control ◽  
Elman Neural Network ◽  
Noise And Vibration ◽  
Nonparametric Approach ◽  
Time Control

The main aim of this paper is to broaden the application’s area of artificial intelligence including fuzzy logic and multiobjective evolutionary algorithm into real-time control area. Wiper system is a high order, nonlinear model with single-input and multi-outputs so that rise time, maximum overshoot, and end-point vibration of wiper blade are observed in conflict as the faster response leads to the larger level of undesired noise and vibration. The first part of this paper centers acquiring experimental data from a passenger automobile wiper system during its operation and using a reliable nonlinear system identification, namely, nonlinear autoregressive exogenous Elman neural network. Knowing that in a practical environment, where the loading conditions of the flexible wiper blade may be varied due to rain, snow, or wind lift in high-speed driving, causing changes in the characteristics of the system, the system performance with a fixed conventional controller scheme will not be satisfactory. The main contribution of this work is presented in second part where a novel multiobjective, bilevel adaptive-fuzzy controller is proposed for an automobile wiper system. The system’s parameters are tuned simultaneously by a multiobjective genetic algorithm based on fitness sharing whereby an automobile wiper blade is moved within its sweep workspace in the least amount of time with minimum noise and vibration.

A real-time control method-based simulation for high-speed trains on large-scale rail network

2017 ◽  
Vol 28 (10) ◽  
pp. 1750126 ◽  
Author(s):  
Yutong Liu ◽  
Chengxuan Cao ◽  
Yaling Zhou ◽  
Ziyan Feng
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
High Speed ◽  
Large Scale ◽  
Simulation Method ◽  
Real Time Control ◽  
Rail Network ◽  
Time Control ◽  
High Speed Trains ◽  
Rail Traffic

In this paper, an improved real-time control model based on the discrete-time method is constructed to control and simulate the movement of high-speed trains on large-scale rail network. The constraints of acceleration and deceleration are introduced in this model, and a more reasonable definition of the minimal headway is also presented. Considering the complicated rail traffic environment in practice, we propose a set of sound operational strategies to excellently control traffic flow on rail network under various conditions. Several simulation experiments with different parameter combinations are conducted to verify the effectiveness of the control simulation method. The experimental results are similar to realistic environment and some characteristics of rail traffic flow are also investigated, especially the impact of stochastic disturbances and the minimal headway on the rail traffic flow on large-scale rail network, which can better assist dispatchers in analysis and decision-making. Meanwhile, experimental results also demonstrate that the proposed control simulation method can be in real-time control of traffic flow for high-speed trains not only on the simple rail line, but also on the complicated large-scale network such as China’s high-speed rail network and serve as a tool of simulating the traffic flow on large-scale rail network to study the characteristics of rail traffic flow.

Research on Fuzzy Control of Mine Ventilation Based on Embedded Systems

2014 ◽  
Vol 686 ◽  
pp. 126-131
Author(s):  
Xiao Yan Sha
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Control Unit ◽  
Real Time Control ◽  
Embedded Processor ◽  
Feed Forward ◽  
Time Control ◽  
Software And Hardware

Taking embedded processor as the core control unit, the paper designs the fan monitoring system software and hardware to achieve the fan working condition detection and real-time control. For the control algorithm, the paper analyzes the fuzzy control system theory and composition, and then combined with tunnel ventilation particularity, introduce feed-forward model to predict the incremental acquisition of pollutants to reduce lag, combined with the system feedback value and the set value, by calculate of two independent computing fuzzy controller, and ultimately determine the number of units increase or decrease in the tunnel jet fans start and stop. Through simulation analysis, the introduction of a feed-forward signal, it can more effectively improve the capability of the system impact of interference.

Optimal Design for Fuzzy Controller by Ant Colony Algorithm

2010 ◽  
Vol 439-440 ◽  
pp. 1190-1196 ◽  
Author(s):  
Bao Jiang Zhao
Keyword(s):  
Ant Colony Algorithm ◽  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Ant Colony ◽  
Fuzzy Rules ◽  
Real Time Control ◽  
Time Control ◽  
Information Updating ◽  
Fuzzy Logical

Fuzzy logical controller is one of the most important applications of fuzzy-rule-based system that models the human decision processing with a collection of fuzzy rules. In this paper, an adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating. The algorithm is used to design a fuzzy logical controller automatically for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. Experimental results show that the designed controller can control actual inverted pendulum successfully.

scholarly journals Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2872 ◽  
Author(s):  
Mokhles M. Abdulghani ◽  
Kasim M. Al-Aubidy ◽  
Mohammed M. Ali ◽  
Qadri J. Hamarsheh
Keyword(s):  
Fuzzy Controller ◽  
Tracking System ◽  
Voice Recognition ◽  
Real Data ◽  
Communication Technologies ◽  
Real Time Control ◽  
Time Control ◽  
Smart Wheelchairs ◽  
Neuro Fuzzy ◽  
The Disabled

Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

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