Knowledge Acquisition of Control Strategy and Tactics for Collision Avoidance Using Fuzzy Neural Networks

An acquisition of operator's rules for collision avoidance using fuzzy neural networks

The procedure for acquiring control rules to improve the performance of control systems has received considerable attention recently. This paper deals with a collision avoidance problem in which the controlled object is a ship with inertia which must avoid collision with a moving object. It has proven to be difficult to obtain collision avoidance rules, i.e., steering rules and speed control ru...

Reactive Collision Avoidance using Evolutionary Neural Networks

Collision avoidance systems can play a vital role in reducing the number of accidents and saving human lives. In this paper, we introduce and validate a novel method for vehicles reactive collision avoidance using evolutionary neural networks (ENN). A single front-facing rangefinder sensor is the only input required by our method. The training process and the proposed method analysis and valida...

development and implementation of an optimized control strategy for induction machine in an electric vehicle

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

Collision Avoidance Using Neural Networks Learned by Genetic Algorithms

As Air Traac keeps increasing, many research programs focus on collision avoidance techniques. In this paper, a neural network learned by genetic algorithm is introduced to solve connicts between two aircraft. The learned NN is then tested on diierent connicts and compared to the optimal solution. Results are very promising. 1 Air Traac Control and Collision Avoidance As Air Traac keeps increas...

Using Heterogeneous Networks for Intersection Collision Avoidance