Lakhmissi Cherroun

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This paper presents a navigation method for an autonomous mobile robot. In order to equip the robot by capability of autonomy and intelligence in its environment, the control system must perform many complex information processing tasks in real time and it is well suited to use the soft-computing techniques. The objective of this paper is to elaborate an(More)
This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the(More)
This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the(More)
One of the standing challenging aspects in mobile robotics is the ability to navigate autonomously. It is a difficult task, which requiring a complete modeling of the environment and intelligent controllers. This paper presents an intelligent navigation method for an autonomous mobile robot which requires only a scalar signal likes a feedback indicating the(More)
One of the standing challenging aspects in mobile robotics is the ability to navigate autonomously. It is a difficult task, which requiring a complete modeling of the environment. This paper presents an intelligent navigation method for an autonomous mobile robot which requires only a scalar signal like a feedback indicating the quality of the applied(More)
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