A Takagi-Sugeno fuzzy controller and an interpolative fuzzy controller for tire slip control in Anti-lock braking Systems are proposed. Both fuzzy controllers are developed using a benchmark consisting of a simplified nonlinear model describing the slip dynamics for a wheel, and perform the merge between 64 local PI or PID controllers. By employing local linearized models of the controlled plant, the local controllers are developed in the frequency

This paper is proposing a new method of on-line evaluation of the weariness of the railway coach disk brakes. The method is using a real-time internal model of the railway coach, able to estimate on-line the speeds of the vehicle and of the wheels even when they are sliding, the braking force, knowing the actual brake cylinder pressure, and the position of the vehicle. A 2D look-up table is modeling the non-linear weariness ratio. It has as inputs

The paper presents a smart sensor of the wheel-rail adherence, a pan of a smart sensor of the velocity of the railway coach during ABS braking. The sliding of the wheels, which are loosing their contact with the rail, induces a total uncertainty over our knowledge about the velocity of the car, since the sensors of the wheels do not show it anymore. An accelerometer is included into the structure of the smart sensor, merged by means of a fuzzy controller

After receiving a piece of evidence Π, intelligent agents adapt their belief state. Knowing the belief state of several sensor agents, a fusion agent forms its own belief state. A belief state (old or new) is characterized by numbers μ(A) attached to subsets A of the universe of worlds. (Usually μ(A) is interpreted as that part of the belief of an agent in the sentence "the actual world belongs to A" and not in any sentence "the actual world belongs