HYBRID SELF-ORGANIZING MAP AND LOCALLY RECURRENT NEURAL NETWORK-BASED ADAPTIVE BACK THROUGH FOR IMPROVING INTEGRATED VEHICLE STABILITY CONTROL

2012 ◽  
Vol 32 (2) ◽  
Author(s):  
Mohamed Harly ◽  
Ida N. Sutantra ◽  
Mauridhi H. Purnomo
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Stability Control ◽  
Vehicle Stability ◽  
Self Organizing Map ◽  
Vehicle Stability Control ◽  
Locally Recurrent ◽  
Self Organizing

Learning and Extracting Initial Mealy Automata with a Modular Neural Network Model

1995 ◽  
Vol 7 (4) ◽  
pp. 822-844 ◽  
Author(s):  
Peter Tiňo ◽  
Jozef Šajda
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Recurrent Network ◽  
Neural Net ◽  
Self Organizing Map ◽  
Training Samples ◽  
Mealy Automata ◽  
Mealy Machine ◽  
Input Strings ◽  
Self Organizing

A hybrid recurrent neural network is shown to learn small initial mealy machines (that can be thought of as translation machines translating input strings to corresponding output strings, as opposed to recognition automata that classify strings as either grammatical or nongrammatical) from positive training samples. A well-trained neural net is then presented once again with the training set and a Kohonen self-organizing map with the “star” topology of neurons is used to quantize recurrent network state space into distinct regions representing corresponding states of a mealy machine being learned. This enables us to extract the learned mealy machine from the trained recurrent network. One neural network (Kohonen self-organizing map) is used to extract meaningful information from another network (recurrent neural network).

An Automatic Tamil Speech Recognition system by using Bidirectional Recurrent Neural Network with Self-Organizing Map

2018 ◽  
Vol 31 (5) ◽  
pp. 1521-1531 ◽  
Author(s):  
S. Lokesh ◽  
Priyan Malarvizhi Kumar ◽  
M. Ramya Devi ◽  
P. Parthasarathy ◽  
C. Gokulnath
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Recurrent Neural Network ◽  
Recognition System ◽  
Speech Recognition System ◽  
Self Organizing Map ◽  
Self Organizing

Adaptive neural network sliding mode control for steer-by-wire-based vehicle stability control

2016 ◽  
Vol 31 (2) ◽  
pp. 885-902 ◽  
Author(s):  
Hai Wang ◽  
Ping He ◽  
Ming Yu ◽  
Linfeng Liu ◽  
Manh Tuan Do ◽  
...  
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Stability Control ◽  
Vehicle Stability ◽  
Adaptive Neural Network ◽  
Mode Control ◽  
Vehicle Stability Control ◽  
Steer By Wire

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

A Novel Stable Locally Recurrent Neural Network with Pole Assignment Projection Approach

2012 ◽  
Vol 38 (2) ◽  
pp. 183-196
Author(s):  
Jian SUN ◽  
Yi CHAI ◽  
Hua-Feng LI ◽  
Zhi-Qin ZHU
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Pole Assignment ◽  
Locally Recurrent ◽  
Projection Approach

Vehicle Stability Control Through Predictive and Optimal Tire Saturation Management

2012 ◽  
Author(s):  
Justin Sill ◽  
Beshah Ayalew
Keyword(s):  
Stability Control ◽  
Vehicle Stability ◽  
Distribution Problem ◽  
Scale Separation ◽  
Torque Distribution ◽  
Hydraulic Hybrid ◽  
Time Scale Separation ◽  
Vehicle Stability Control ◽  
Natural Time ◽  
Set Up

This paper presents a predictive vehicle stability control (VSC) strategy that distributes the drive/braking torques to each wheel of the vehicle based on the optimal exploitation of the available traction capability for each tire. To this end, tire saturation levels are defined as the deficiency of a tire to generate a force that linearly increases with the relevant slip quantities. These saturation levels are then used to set up an optimization objective for a torque distribution problem within a novel cascade control structure that exploits the natural time scale separation of the slower lateral handling dynamics of the vehicle from the relatively faster rotational dynamics of the wheel/tire. The envisaged application of the proposed vehicle stability strategy is for vehicles with advanced and emerging pure electric, hybrid electric or hydraulic hybrid power trains featuring independent wheel drives. The developed predictive control strategy is evaluated for, a two-axle truck featuring such an independent drive system and subjected to a transient handling maneuver.

Classification of salt-contaminated velocities with self-organizing map neural network

2002 ◽  
Vol 21 (12) ◽  
pp. 1193-1196 ◽  
Author(s):  
Lin Zhang ◽  
Al Fortier ◽  
David C. Bartel
Keyword(s):  
Neural Network ◽  
Self Organizing Map ◽  
Self Organizing
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