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This paper proposes an efficient neural network (NN) controller for the tracking control of an autonomous underwater vehicles (AUV) subject to unknown vehicle dynamics and significant uncertainties. The controller is first designed based on the error dynamics by using backstepping technique. Then, the unknown dynamics and uncertainties of the vehicle are handled by introducing a NN with single-layer...
This paper presents a new path planning method for mobile robots in unknown environments. The structure of the proposed algorithm is a hybrid fuzzy logic neural networks, and hence it benefits from the potentials of these two techniques. For modeling the mobile robot, the proposed system adopts the Braitenberg's automata models that were developed for agents. Wheels of the robot are represented by...
Detecting and monitoring odour around livestock farms are difficult. In this paper, a dynamic neural network based model is proposed to locate odour dispersion around livestock facilities. The proposed dispersion model can dynamically represent complex or non-steady-state meteorological and topographical features in and around livestock farm areas. The proposed approach can also model odour dispersions...
In this paper, an improved self organizing map (SOM)-based approach is proposed for multi-robot systems to tackle the task assignment problem which focuses on the self-organization issue with a large number of robots and a large number of task locations in dynamic environments subject to uncertainties. It is capable of dynamically controlling a group of mobile robots to achieve different task locations...
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